Sample records for machine tool structure

  1. Graphite fiber reinforced structure for supporting machine tools

    DOEpatents

    Knight, Jr., Charles E.; Kovach, Louis; Hurst, John S.

    1978-01-01

    Machine tools utilized in precision machine operations require tool support structures which exhibit minimal deflection, thermal expansion and vibration characteristics. The tool support structure of the present invention is a graphite fiber reinforced composite in which layers of the graphite fibers or yarn are disposed in a 0/90.degree. pattern and bonded together with an epoxy resin. The finished composite possesses a low coefficient of thermal expansion and a substantially greater elastic modulus, stiffness-to-weight ratio, and damping factor than a conventional steel tool support utilized in similar machining operations.

  2. Vibration Damping Analysis of Lightweight Structures in Machine Tools

    PubMed Central

    Aggogeri, Francesco; Borboni, Alberto; Merlo, Angelo; Pellegrini, Nicola; Ricatto, Raffaele

    2017-01-01

    The dynamic behaviour of a machine tool (MT) directly influences the machining performance. The adoption of lightweight structures may reduce the effects of undesired vibrations and increase the workpiece quality. This paper aims to present and compare a set of hybrid materials that may be excellent candidates to fabricate the MT moving parts. The selected materials have high dynamic characteristics and capacity to dampen mechanical vibrations. In this way, starting from the kinematic model of a milling machine, this study evaluates a number of prototypes made of Al foam sandwiches (AFS), Al corrugated sandwiches (ACS) and composite materials reinforced by carbon fibres (CFRP). These prototypes represented the Z-axis ram of a commercial milling machine. The static and dynamical properties have been analysed by using both finite element (FE) simulations and experimental tests. The obtained results show that the proposed structures may be a valid alternative to the conventional materials of MT moving parts, increasing machining performance. In particular, the AFS prototype highlighted a damping ratio that is 20 times greater than a conventional ram (e.g., steel). Its application is particularly suitable to minimize unwanted oscillations during high-speed finishing operations. The results also show that the CFRP structure guarantees high stiffness with a weight reduced by 48.5%, suggesting effective applications in roughing operations, saving MT energy consumption. The ACS structure has a good trade-off between stiffness and damping and may represent a further alternative, if correctly evaluated. PMID:28772653

  3. Machine tool locator

    DOEpatents

    Hanlon, John A.; Gill, Timothy J.

    2001-01-01

    Machine tools can be accurately measured and positioned on manufacturing machines within very small tolerances by use of an autocollimator on a 3-axis mount on a manufacturing machine and positioned so as to focus on a reference tooling ball or a machine tool, a digital camera connected to the viewing end of the autocollimator, and a marker and measure generator for receiving digital images from the camera, then displaying or measuring distances between the projection reticle and the reference reticle on the monitoring screen, and relating the distances to the actual position of the autocollimator relative to the reference tooling ball. The images and measurements are used to set the position of the machine tool and to measure the size and shape of the machine tool tip, and examine cutting edge wear. patent

  4. Machine tool task force

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sutton, G.P.

    1980-10-22

    The Machine Tool Task Force (MTTF) is a multidisciplined team of international experts, whose mission was to investigate the state of the art of machine tool technology, to identify promising future directions of that technology for both the US government and private industry, and to disseminate the findings of its research in a conference and through the publication of a final report. MTTF was a two and one-half year effort that involved the participation of 122 experts in the specialized technologies of machine tools and in the management of machine tool operations. The scope of the MTTF was limited tomore » cutting-type or material-removal-type machine tools, because they represent the major share and value of all machine tools now installed or being built. The activities of the MTTF and the technical, commercial and economic signifiance of recommended activities for improving machine tool technology are discussed. (LCL)« less

  5. Technology of machine tools. Volume 4. Machine tool controls

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Not Available

    1980-10-01

    The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

  6. Technology of machine tools. Volume 3. Machine tool mechanics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tlusty, J.

    1980-10-01

    The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

  7. Technology of machine tools. Volume 5. Machine tool accuracy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hocken, R.J.

    1980-10-01

    The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

  8. Nanocomposites for Machining Tools

    PubMed Central

    Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

    2017-01-01

    Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance. PMID:29027926

  9. Machine Tool Software

    NASA Technical Reports Server (NTRS)

    1988-01-01

    A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

  10. Modelling of Tool Wear and Residual Stress during Machining of AISI H13 Tool Steel

    NASA Astrophysics Data System (ADS)

    Outeiro, José C.; Umbrello, Domenico; Pina, José C.; Rizzuti, Stefania

    2007-05-01

    Residual stresses can enhance or impair the ability of a component to withstand loading conditions in service (fatigue, creep, stress corrosion cracking, etc.), depending on their nature: compressive or tensile, respectively. This poses enormous problems in structural assembly as this affects the structural integrity of the whole part. In addition, tool wear issues are of critical importance in manufacturing since these affect component quality, tool life and machining cost. Therefore, prediction and control of both tool wear and the residual stresses in machining are absolutely necessary. In this work, a two-dimensional Finite Element model using an implicit Lagrangian formulation with an automatic remeshing was applied to simulate the orthogonal cutting process of AISI H13 tool steel. To validate such model the predicted and experimentally measured chip geometry, cutting forces, temperatures, tool wear and residual stresses on the machined affected layers were compared. The proposed FE model allowed us to investigate the influence of tool geometry, cutting regime parameters and tool wear on residual stress distribution in the machined surface and subsurface of AISI H13 tool steel. The obtained results permit to conclude that in order to reduce the magnitude of surface residual stresses, the cutting speed should be increased, the uncut chip thickness (or feed) should be reduced and machining with honed tools having large cutting edge radii produce better results than chamfered tools. Moreover, increasing tool wear increases the magnitude of surface residual stresses.

  11. Standardized Curriculum for Machine Tool Operation/Machine Shop.

    ERIC Educational Resources Information Center

    Mississippi State Dept. of Education, Jackson. Office of Vocational, Technical and Adult Education.

    Standardized vocational education course titles and core contents for two courses in Mississippi are provided: machine tool operation/machine shop I and II. The first course contains the following units: (1) orientation; (2) shop safety; (3) shop math; (4) measuring tools and instruments; (5) hand and bench tools; (6) blueprint reading; (7)…

  12. Diamond machine tool face lapping machine

    DOEpatents

    Yetter, H.H.

    1985-05-06

    An apparatus for shaping, sharpening and polishing diamond-tipped single-point machine tools. The isolation of a rotating grinding wheel from its driving apparatus using an air bearing and causing the tool to be shaped, polished or sharpened to be moved across the surface of the grinding wheel so that it does not remain at one radius for more than a single rotation of the grinding wheel has been found to readily result in machine tools of a quality which can only be obtained by the most tedious and costly processing procedures, and previously unattainable by simple lapping techniques.

  13. Technology of machine tools. Volume 2. Machine tool systems management and utilization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Thomson, A.R.

    1980-10-01

    The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

  14. Machine tools and fixtures: A compilation

    NASA Technical Reports Server (NTRS)

    1971-01-01

    As part of NASA's Technology Utilizations Program, a compilation was made of technological developments regarding machine tools, jigs, and fixtures that have been produced, modified, or adapted to meet requirements of the aerospace program. The compilation is divided into three sections that include: (1) a variety of machine tool applications that offer easier and more efficient production techniques; (2) methods, techniques, and hardware that aid in the setup, alignment, and control of machines and machine tools to further quality assurance in finished products: and (3) jigs, fixtures, and adapters that are ancillary to basic machine tools and aid in realizing their greatest potential.

  15. Slide system for machine tools

    DOEpatents

    Douglass, S.S.; Green, W.L.

    1980-06-12

    The present invention relates to a machine tool which permits the machining of nonaxisymmetric surfaces on a workpiece while rotating the workpiece about a central axis of rotation. The machine tool comprises a conventional two-slide system (X-Y) with one of these slides being provided with a relatively short travel high-speed auxiliary slide which carries the material-removing tool. The auxiliary slide is synchronized with the spindle speed and the position of the other two slides and provides a high-speed reciprocating motion required for the displacement of the cutting tool for generating a nonaxisymmetric surface at a selected location on the workpiece.

  16. Slide system for machine tools

    DOEpatents

    Douglass, Spivey S.; Green, Walter L.

    1982-01-01

    The present invention relates to a machine tool which permits the machining of nonaxisymmetric surfaces on a workpiece while rotating the workpiece about a central axis of rotation. The machine tool comprises a conventional two-slide system (X-Y) with one of these slides being provided with a relatively short travel high-speed auxiliary slide which carries the material-removing tool. The auxiliary slide is synchronized with the spindle speed and the position of the other two slides and provides a high-speed reciprocating motion required for the displacement of the cutting tool for generating a nonaxisymmetric surface at a selected location on the workpiece.

  17. Chip breaking system for automated machine tool

    DOEpatents

    Arehart, Theodore A.; Carey, Donald O.

    1987-01-01

    The invention is a rotary selectively directional valve assembly for use in an automated turret lathe for directing a stream of high pressure liquid machining coolant to the interface of a machine tool and workpiece for breaking up ribbon-shaped chips during the formation thereof so as to inhibit scratching or other marring of the machined surfaces by these ribbon-shaped chips. The valve assembly is provided by a manifold arrangement having a plurality of circumferentially spaced apart ports each coupled to a machine tool. The manifold is rotatable with the turret when the turret is positioned for alignment of a machine tool in a machining relationship with the workpiece. The manifold is connected to a non-rotational header having a single passageway therethrough which conveys the high pressure coolant to only the port in the manifold which is in registry with the tool disposed in a working relationship with the workpiece. To position the machine tools the turret is rotated and one of the tools is placed in a material-removing relationship of the workpiece. The passageway in the header and one of the ports in the manifold arrangement are then automatically aligned to supply the machining coolant to the machine tool workpiece interface for breaking up of the chips as well as cooling the tool and workpiece during the machining operation.

  18. A method to identify the main mode of machine tool under operating conditions

    NASA Astrophysics Data System (ADS)

    Wang, Daming; Pan, Yabing

    2017-04-01

    The identification of the modal parameters under experimental conditions is the most common procedure when solving the problem of machine tool structure vibration. However, the influence of each mode on the machine tool vibration in real working conditions remains unknown. In fact, the contributions each mode makes to the machine tool vibration during machining process are different. In this article, an active excitation modal analysis is applied to identify the modal parameters in operational condition, and the Operating Deflection Shapes (ODS) in frequencies of high level vibration that affect the quality of machining in real working conditions are obtained. Then, the ODS is decomposed by the mode shapes which are identified in operational conditions. So, the contributions each mode makes to machine tool vibration during machining process are got by decomposition coefficients. From the previous steps, we can find out the main modes which effect the machine tool more significantly in working conditions. This method was also verified to be effective by experiments.

  19. Overview of the Machine-Tool Task Force

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sutton, G.P.

    1981-06-08

    The Machine Tool Task Force, (MTTF) surveyed the state of the art of machine tool technology for material removal for two and one-half years. This overview gives a brief summary of the approach, specific subjects covered, principal conclusions and some of the key recommendations aimed at improving the technology and advancing the productivity of machine tools. The Task Force consisted of 123 experts from the US and other countries. Their findings are documented in a five-volume report, Technology of Machine Tools.

  20. A Real-Time Tool Positioning Sensor for Machine-Tools

    PubMed Central

    Ruiz, Antonio Ramon Jimenez; Rosas, Jorge Guevara; Granja, Fernando Seco; Honorato, Jose Carlos Prieto; Taboada, Jose Juan Esteve; Serrano, Vicente Mico; Jimenez, Teresa Molina

    2009-01-01

    In machining, natural oscillations, and elastic, gravitational or temperature deformations, are still a problem to guarantee the quality of fabricated parts. In this paper we present an optical measurement system designed to track and localize in 3D a reference retro-reflector close to the machine-tool's drill. The complete system and its components are described in detail. Several tests, some static (including impacts and rotations) and others dynamic (by executing linear and circular trajectories), were performed on two different machine tools. It has been integrated, for the first time, a laser tracking system into the position control loop of a machine-tool. Results indicate that oscillations and deformations close to the tool can be estimated with micrometric resolution and a bandwidth from 0 to more than 100 Hz. Therefore this sensor opens the possibility for on-line compensation of oscillations and deformations. PMID:22408472

  1. Miniaturized multiwavelength digital holography sensor for extensive in-machine tool measurement

    NASA Astrophysics Data System (ADS)

    Seyler, Tobias; Fratz, Markus; Beckmann, Tobias; Bertz, Alexander; Carl, Daniel

    2017-06-01

    In this paper we present a miniaturized digital holographic sensor (HoloCut) for operation inside a machine tool. With state-of-the-art 3D measurement systems, short-range structures such as tool marks cannot be resolved inside a machine tool chamber. Up to now, measurements had to be conducted outside the machine tool and thus processing data are generated offline. The sensor presented here uses digital multiwavelength holography to get 3D-shape-information of the machined sample. By using three wavelengths, we get a large artificial wavelength with a large unambiguous measurement range of 0.5mm and achieve micron repeatability even in the presence of laser speckles on rough surfaces. In addition, a digital refocusing algorithm based on phase noise is implemented to extend the measurement range beyond the limits of the artificial wavelength and geometrical depth-of-focus. With complex wave field propagation, the focus plane can be shifted after the camera images have been taken and a sharp image with extended depth of focus is constructed consequently. With 20mm x 20mm field of view the sensor enables measurement of both macro- and micro-structure (such as tool marks) with an axial resolution of 1 µm, lateral resolution of 7 µm and consequently allows processing data to be generated online which in turn qualifies it as a machine tool control. To make HoloCut compact enough for operation inside a machining center, the beams are arranged in two planes: The beams are split into reference beam and object beam in the bottom plane and combined onto the camera in the top plane later on. Using a mechanical standard interface according to DIN 69893 and having a very compact size of 235mm x 140mm x 215mm (WxHxD) and a weight of 7.5 kg, HoloCut can be easily integrated into different machine tools and extends no more in height than a typical processing tool.

  2. Towards a generalized energy prediction model for machine tools

    PubMed Central

    Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H.; Dornfeld, David A.; Helu, Moneer; Rachuri, Sudarsan

    2017-01-01

    Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process. PMID:28652687

  3. Towards a generalized energy prediction model for machine tools.

    PubMed

    Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H; Dornfeld, David A; Helu, Moneer; Rachuri, Sudarsan

    2017-04-01

    Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process.

  4. Nanometric edge profile measurement of cutting tools on a diamond turning machine

    NASA Astrophysics Data System (ADS)

    Asai, Takemi; Arai, Yoshikazu; Cui, Yuguo; Gao, Wei

    2008-10-01

    Single crystal diamond tools are used for fabrication of precision parts [1-5]. Although there are many types of tools that are supplied, the tools with round nose are popular for machining very smooth surfaces. Tools with small nose radii, small wedge angles and included angles are also being utilized for fabrication of micro structured surfaces such as microlens arrays [6], diffractive optical elements and so on. In ultra precision machining, tools are very important as a part of the machining equipment. The roughness or profile of machined surface may become out of desired tolerance. It is thus necessary to know the state of the tool edge accurately. To meet these requirements, an atomic force microscope (AFM) for measuring the 3D edge profiles of tools having nanometer-scale cutting edge radii with high resolution has been developed [7-8]. Although the AFM probe unit is combined with an optical sensor for aligning the measurement probe with the tools edge top to be measured in short time in this system, this time only the AFM probe unit was used. During the measurement time, that was attached onto the ultra precision turning machine to confirm the possibility of profile measurement system.

  5. [Research on infrared safety protection system for machine tool].

    PubMed

    Zhang, Shuan-Ji; Zhang, Zhi-Ling; Yan, Hui-Ying; Wang, Song-De

    2008-04-01

    In order to ensure personal safety and prevent injury accident in machine tool operation, an infrared machine tool safety system was designed with infrared transmitting-receiving module, memory self-locked relay and voice recording-playing module. When the operator does not enter the danger area, the system has no response. Once the operator's whole or part of body enters the danger area and shades the infrared beam, the system will alarm and output an control signal to the machine tool executive element, and at the same time, the system makes the machine tool emergency stop to prevent equipment damaged and person injured. The system has a module framework, and has many advantages including safety, reliability, common use, circuit simplicity, maintenance convenience, low power consumption, low costs, working stability, easy debugging, vibration resistance and interference resistance. It is suitable for being installed and used in different machine tools such as punch machine, pour plastic machine, digital control machine, armor plate cutting machine, pipe bending machine, oil pressure machine etc.

  6. Linear positioning laser calibration setup of CNC machine tools

    NASA Astrophysics Data System (ADS)

    Sui, Xiulin; Yang, Congjing

    2002-10-01

    The linear positioning laser calibration setup of CNC machine tools is capable of executing machine tool laser calibraiotn and backlash compensation. Using this setup, hole locations on CNC machien tools will be correct and machien tool geometry will be evaluated and adjusted. Machien tool laser calibration and backlash compensation is a simple and straightforward process. First the setup is to 'find' the stroke limits of the axis. Then the laser head is then brought into correct alignment. Second is to move the machine axis to the other extreme, the laser head is now aligned, using rotation and elevation adjustments. Finally the machine is moved to the start position and final alignment is verified. The stroke of the machine, and the machine compensation interval dictate the amount of data required for each axis. These factors determine the amount of time required for a through compensation of the linear positioning accuracy. The Laser Calibrator System monitors the material temperature and the air density; this takes into consideration machine thermal growth and laser beam frequency. This linear positioning laser calibration setup can be used on CNC machine tools, CNC lathes, horizontal centers and vertical machining centers.

  7. An investigation of chatter and tool wear when machining titanium

    NASA Technical Reports Server (NTRS)

    Sutherland, I. A.

    1974-01-01

    The low thermal conductivity of titanium, together with the low contact area between chip and tool and the unusually high chip velocities, gives rise to high tool tip temperatures and accelerated tool wear. Machining speeds have to be considerably reduced to avoid these high temperatures with a consequential loss of productivity. Restoring this lost productivity involves increasing other machining variables, such as feed and depth-of-cut, and can lead to another machining problem commonly known as chatter. This work is to acquaint users with these problems, to examine the variables that may be encountered when machining a material like titanium, and to advise the machine tool user on how to maximize the output from the machines and tooling available to him. Recommendations are made on ways of improving tolerances, reducing machine tool instability or chatter, and improving productivity. New tool materials, tool coatings, and coolants are reviewed and their relevance examined when machining titanium.

  8. Traceability of On-Machine Tool Measurement: A Review.

    PubMed

    Mutilba, Unai; Gomez-Acedo, Eneko; Kortaberria, Gorka; Olarra, Aitor; Yagüe-Fabra, Jose A

    2017-07-11

    Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand.

  9. Traceability of On-Machine Tool Measurement: A Review

    PubMed Central

    Gomez-Acedo, Eneko; Kortaberria, Gorka; Olarra, Aitor

    2017-01-01

    Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand. PMID:28696358

  10. Research on the tool holder mode in high speed machining

    NASA Astrophysics Data System (ADS)

    Zhenyu, Zhao; Yongquan, Zhou; Houming, Zhou; Xiaomei, Xu; Haibin, Xiao

    2018-03-01

    High speed machining technology can improve the processing efficiency and precision, but also reduce the processing cost. Therefore, the technology is widely regarded in the industry. With the extensive application of high-speed machining technology, high-speed tool system has higher and higher requirements on the tool chuck. At present, in high speed precision machining, several new kinds of clip heads are as long as there are heat shrinkage tool-holder, high-precision spring chuck, hydraulic tool-holder, and the three-rib deformation chuck. Among them, the heat shrinkage tool-holder has the advantages of high precision, high clamping force, high bending rigidity and dynamic balance, etc., which are widely used. Therefore, it is of great significance to research the new requirements of the machining tool system. In order to adapt to the requirement of high speed machining precision machining technology, this paper expounds the common tool holder technology of high precision machining, and proposes how to select correctly tool clamping system in practice. The characteristics and existing problems are analyzed in the tool clamping system.

  11. Identification of Tool Wear when Machining of Austenitic Steels and Titatium by Miniature Machining

    NASA Astrophysics Data System (ADS)

    Pilc, Jozef; Kameník, Roman; Varga, Daniel; Martinček, Juraj; Sadilek, Marek

    2016-12-01

    Application of miniature machining is currently rapidly increasing mainly in biomedical industry and machining of hard-to-machine materials. Machinability of materials with increased level of toughness depends on factors that are important in the final state of surface integrity. Because of this, it is necessary to achieve high precision (varying in microns) in miniature machining. If we want to guarantee machining high precision, it is necessary to analyse tool wear intensity in direct interaction with given machined materials. During long-term cutting process, different cutting wedge deformations occur, leading in most cases to a rapid wear and destruction of the cutting wedge. This article deal with experimental monitoring of tool wear intensity during miniature machining.

  12. Plan for conducting an international machine tool task force

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sutton, G.P.; McClure, E.R.; Schuman, J.F.

    1978-08-28

    The basic objectives of the Machine Tool Task Force (MTTF) are to characterize and summarize the state of the art of cutting machine tool technology and to identify promising areas of future R and D. These goals will be accomplished with a series of multidisciplinary teams of prominent experts and individuals experienced in the specialized technologies of machine tools or in the management of machine tool operations. Experts will be drawn from all areas of the machine tool community: machine tool users or buyer organizations, builders, and R and D establishments including universities and government laboratories, both domestic and foreign.more » A plan for accomplishing this task is presented. The area of machine tool technology has been divided into about two dozen technology subjects on which teams of one or more experts will work. These teams are, in turn, organized into four principal working groups dealing, respectively, with machine tool accuracy, mechanics, control, and management systems/utilization. Details are presented on specific subjects to be covered, the organization of the Task Force and its four working groups, and the basic approach to determining the state of the art of technology and the future directions of this technology. The planned review procedure, the potential benefits, our management approach, and the schedule, as well as the key participating personnel and their background are discussed. The initial meeting of MTTF members will be held at a plenary session on October 16 and 17, 1978, in Scottsdale, AZ. The MTTF study will culminate in a conference on September 1, 1980, in Chicago, IL, immediately preceeding the 1980 International Machine Tool Show. At this time, our results will be released to the public; a series of reports will be published in late 1980.« less

  13. Parameter identification and optimization of slide guide joint of CNC machine tools

    NASA Astrophysics Data System (ADS)

    Zhou, S.; Sun, B. B.

    2017-11-01

    The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

  14. Method for machining steel with diamond tools

    DOEpatents

    Casstevens, J.M.

    1984-01-01

    The present invention is directed to a method for machine optical quality finishes and contour accuracies of workpieces of carbon-containing metals such as steel with diamond tooling. The wear rate of the diamond tooling is significantly reduced by saturating the atmosphere at the interface of the workpiece and the diamond tool with a gaseous hydrocarbon during the machining operation. The presence of the gaseous hydrocarbon effectively eliminates the deterioration of the diamond tool by inhibiting or preventing the conversion of the diamond carbon to graphite carbon at the point of contact between the cutting tool and the workpiece.

  15. Method for machining steel with diamond tools

    DOEpatents

    Casstevens, John M.

    1986-01-01

    The present invention is directed to a method for machining optical quality inishes and contour accuracies of workpieces of carbon-containing metals such as steel with diamond tooling. The wear rate of the diamond tooling is significantly reduced by saturating the atmosphere at the interface of the workpiece and the diamond tool with a gaseous hydrocarbon during the machining operation. The presence of the gaseous hydrocarbon effectively eliminates the deterioration of the diamond tool by inhibiting or preventing the conversion of the diamond carbon to graphite carbon at the point of contact between the cutting tool and the workpiece.

  16. Material Choice for spindle of machine tools

    NASA Astrophysics Data System (ADS)

    Gouasmi, S.; Merzoug, B.; Abba, G.; Kherredine, L.

    2012-02-01

    The requirements of contemporary industry and the flashing development of modern sciences impose restrictions on the majority of the elements of machines; the resulting financial constraints can be satisfied by a better output of the production equipment. As for those concerning the design, the resistance and the correct operation of the product, these require the development of increasingly precise parts, therefore the use of increasingly powerful tools [5]. The precision of machining and the output of the machine tools are generally determined by the precision of rotation of the spindle, indeed, more this one is large more the dimensions to obtain are in the zone of tolerance and the defects of shape are minimized. During the development of the machine tool, the spindle which by definition is a rotating shaft receiving and transmitting to the work piece or the cutting tool the rotational movement, must be designed according to certain optimal parameters to be able to ensure the precision required. This study will be devoted to the choice of the material of the spindle fulfilling the imposed requirements of precision.

  17. Mississippi Curriculum Framework for Machine Tool Operation/Machine Shop and Tool and Die Making Technology Cluster (Program CIP: 48.0507--Tool and Die Maker/Technologist) (Program CIP: 48.0503--Machine Shop Assistant). Postsecondary Programs.

    ERIC Educational Resources Information Center

    Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

    This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for the course sequences in the machine tool operation/machine tool and tool and die making technology programs cluster. Presented in the introductory section are a framework of courses and programs, description of the…

  18. Evaluation of machine learning tools for inspection of steam generator tube structures using pulsed eddy current

    NASA Astrophysics Data System (ADS)

    Buck, J. A.; Underhill, P. R.; Morelli, J.; Krause, T. W.

    2017-02-01

    Degradation of nuclear steam generator (SG) tubes and support structures can result in a loss of reactor efficiency. Regular in-service inspection, by conventional eddy current testing (ECT), permits detection of cracks, measurement of wall loss, and identification of other SG tube degradation modes. However, ECT is challenged by overlapping degradation modes such as might occur for SG tube fretting accompanied by tube off-set within a corroding ferromagnetic support structure. Pulsed eddy current (PEC) is an emerging technology examined here for inspection of Alloy-800 SG tubes and associated carbon steel drilled support structures. Support structure hole size was varied to simulate uniform corrosion, while SG tube was off-set relative to hole axis. PEC measurements were performed using a single driver with an 8 pick-up coil configuration in the presence of flat-bottom rectangular frets as an overlapping degradation mode. A modified principal component analysis (MPCA) was performed on the time-voltage data in order to reduce data dimensionality. The MPCA scores were then used to train a support vector machine (SVM) that simultaneously targeted four independent parameters associated with; support structure hole size, tube off-centering in two dimensions and fret depth. The support vector machine was trained, tested, and validated on experimental data. Results were compared with a previously developed artificial neural network (ANN) trained on the same data. Estimates of tube position showed comparable results between the two machine learning tools. However, the ANN produced better estimates of hole inner diameter and fret depth. The better results from ANN analysis was attributed to challenges associated with the SVM when non-constant variance is present in the data.

  19. Volumetric Verification of Multiaxis Machine Tool Using Laser Tracker

    PubMed Central

    Aguilar, Juan José

    2014-01-01

    This paper aims to present a method of volumetric verification in machine tools with linear and rotary axes using a laser tracker. Beyond a method for a particular machine, it presents a methodology that can be used in any machine type. Along this paper, the schema and kinematic model of a machine with three axes of movement, two linear and one rotational axes, including the measurement system and the nominal rotation matrix of the rotational axis are presented. Using this, the machine tool volumetric error is obtained and nonlinear optimization techniques are employed to improve the accuracy of the machine tool. The verification provides a mathematical, not physical, compensation, in less time than other methods of verification by means of the indirect measurement of geometric errors of the machine from the linear and rotary axes. This paper presents an extensive study about the appropriateness and drawbacks of the regression function employed depending on the types of movement of the axes of any machine. In the same way, strengths and weaknesses of measurement methods and optimization techniques depending on the space available to place the measurement system are presented. These studies provide the most appropriate strategies to verify each machine tool taking into consideration its configuration and its available work space. PMID:25202744

  20. Study on electroplating technology of diamond tools for machining hard and brittle materials

    NASA Astrophysics Data System (ADS)

    Cui, Ying; Chen, Jian Hua; Sun, Li Peng; Wang, Yue

    2016-10-01

    With the development of the high speed cutting, the ultra-precision machining and ultrasonic vibration technique in processing hard and brittle material , the requirement of cutting tools is becoming higher and higher. As electroplated diamond tools have distinct advantages, such as high adaptability, high durability, long service life and good dimensional stability, the cutting tools are effective and extensive used in grinding hard and brittle materials. In this paper, the coating structure of electroplating diamond tool is described. The electroplating process flow is presented, and the influence of pretreatment on the machining quality is analyzed. Through the experimental research and summary, the reasonable formula of the electrolyte, the electroplating technologic parameters and the suitable sanding method were determined. Meanwhile, the drilling experiment on glass-ceramic shows that the electroplating process can effectively improve the cutting performance of diamond tools. It has laid a good foundation for further improving the quality and efficiency of the machining of hard and brittle materials.

  1. Speed-Selector Guard For Machine Tool

    NASA Technical Reports Server (NTRS)

    Shakhshir, Roda J.; Valentine, Richard L.

    1992-01-01

    Simple guardplate prevents accidental reversal of direction of rotation or sudden change of speed of lathe, milling machine, or other machine tool. Custom-made for specific machine and control settings. Allows control lever to be placed at only one setting. Operator uses handle to slide guard to engage or disengage control lever. Protects personnel from injury and equipment from damage occurring if speed- or direction-control lever inadvertently placed in wrong position.

  2. Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

    NASA Astrophysics Data System (ADS)

    Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

    2017-08-01

    This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

  3. Method and apparatus for characterizing and enhancing the dynamic performance of machine tools

    DOEpatents

    Barkman, William E; Babelay, Jr., Edwin F

    2013-12-17

    Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include dynamic one axis positional accuracy of the machine tool, dynamic cross-axis stability of the machine tool, and dynamic multi-axis positional accuracy of the machine tool.

  4. Machine Tool Series. Duty Task List.

    ERIC Educational Resources Information Center

    Oklahoma State Dept. of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

    This task list is intended for use in planning and/or evaluating a competency-based course to prepare machine tool, drill press, grinding machine, lathe, mill, and/or power saw operators. The listing is divided into six sections, with each one outlining the tasks required to perform the duties that have been identified for the given occupation.…

  5. Technology of machine tools. Volume 1. Executive summary

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sutton, G.P.

    1980-10-01

    The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

  6. Process Damping and Cutting Tool Geometry in Machining

    NASA Astrophysics Data System (ADS)

    Taylor, C. M.; Sims, N. D.; Turner, S.

    2011-12-01

    Regenerative vibration, or chatter, limits the performance of machining processes. Consequences of chatter include tool wear and poor machined surface finish. Process damping by tool-workpiece contact can reduce chatter effects and improve productivity. Process damping occurs when the flank (also known as the relief face) of the cutting tool makes contact with waves on the workpiece surface, created by chatter motion. Tool edge features can act to increase the damping effect. This paper examines how a tool's edge condition combines with the relief angle to affect process damping. An analytical model of cutting with chatter leads to a two-section curve describing how process damped vibration amplitude changes with surface speed for radiussed tools. The tool edge dominates the process damping effect at the lowest surface speeds, with the flank dominating at higher speeds. A similar curve is then proposed regarding tools with worn edges. Experimental data supports the notion of the two-section curve. A rule of thumb is proposed which could be useful to machine operators, regarding tool wear and process damping. The question is addressed, should a tool of a given geometry, used for a given application, be considered as sharp, radiussed or worn regarding process damping.

  7. Sine-Bar Attachment For Machine Tools

    NASA Technical Reports Server (NTRS)

    Mann, Franklin D.

    1988-01-01

    Sine-bar attachment for collets, spindles, and chucks helps machinists set up quickly for precise angular cuts that require greater precision than provided by graduations of machine tools. Machinist uses attachment to index head, carriage of milling machine or lathe relative to table or turning axis of tool. Attachment accurate to 1 minute or arc depending on length of sine bar and precision of gauge blocks in setup. Attachment installs quickly and easily on almost any type of lathe or mill. Requires no special clamps or fixtures, and eliminates many trial-and-error measurements. More stable than improvised setups and not jarred out of position readily.

  8. Method and apparatus for suppressing regenerative instability and related chatter in machine tools

    DOEpatents

    Segalman, Daniel J.; Redmond, James M.

    2001-01-01

    Methods of and apparatuses for mitigating chatter vibrations in machine tools or components thereof. Chatter therein is suppressed by periodically or continuously varying the stiffness of the cutting tool (or some component of the cutting tool), and hence the resonant frequency of the cutting tool (or some component thereof). The varying of resonant frequency of the cutting tool can be accomplished by modulating the stiffness of the cutting tool, the cutting tool holder, or any other component of the support for the cutting tool. By periodically altering the impedance of the cutting tool assembly, chatter is mitigated. In one embodiment, a cyclic electric (or magnetic) field is applied to the spindle quill which contains an electro-rheological (or magneto-rheological) fluid. The variable yield stress in the fluid affects the coupling of the spindle to the machine tool structure, changing the natural frequency of oscillation. Altering the modal characteristics in this fashion disrupts the modulation of current tool vibrations with previous tool vibrations recorded on the workpiece surface.

  9. Method and apparatus for suppressing regenerative instability and related chatter in machine tools

    DOEpatents

    Segalman, Daniel J.; Redmond, James M.

    1999-01-01

    Methods of and apparatuses for mitigating chatter vibrations in machine tools or components thereof. Chatter therein is suppressed by periodically or continuously varying the stiffness of the cutting tool (or some component of the cutting tool), and hence the resonant frequency of the cutting tool (or some component thereof). The varying of resonant frequency of the cutting tool can be accomplished by modulating the stiffness of the cutting tool, the cutting tool holder, or any other component of the support for the cutting tool. By periodically altering the impedance of the cutting tool assembly, chatter is mitigated. In one embodiment, a cyclic electric (or magnetic) field is applied to the spindle quill which contains an electro-rheological (or magneto-rheological) fluid. The variable yield stress in the fluid affects the coupling of the spindle to the machine tool structure, changing the natural frequency of oscillation. Altering the modal characteristics in this fashion disrupts the modulation of current tool vibrations with previous tool vibrations recorded on the workpiece surface.

  10. Heat treatment stabilizes welded aluminum jigs and tool structures

    NASA Technical Reports Server (NTRS)

    Mehnert, R. S.

    1966-01-01

    Heat treatment processes, applied after welding but before machining, imparts above normal stability to welded aluminum jigs and tool structures. Weight saving will not be realized in these tools if rigidity equal to that of a comparable steel tool is required.

  11. Actualities and Development of Heavy-Duty CNC Machine Tool Thermal Error Monitoring Technology

    NASA Astrophysics Data System (ADS)

    Zhou, Zu-De; Gui, Lin; Tan, Yue-Gang; Liu, Ming-Yao; Liu, Yi; Li, Rui-Ya

    2017-09-01

    Thermal error monitoring technology is the key technological support to solve the thermal error problem of heavy-duty CNC (computer numerical control) machine tools. Currently, there are many review literatures introducing the thermal error research of CNC machine tools, but those mainly focus on the thermal issues in small and medium-sized CNC machine tools and seldom introduce thermal error monitoring technologies. This paper gives an overview of the research on the thermal error of CNC machine tools and emphasizes the study of thermal error of the heavy-duty CNC machine tool in three areas. These areas are the causes of thermal error of heavy-duty CNC machine tool and the issues with the temperature monitoring technology and thermal deformation monitoring technology. A new optical measurement technology called the "fiber Bragg grating (FBG) distributed sensing technology" for heavy-duty CNC machine tools is introduced in detail. This technology forms an intelligent sensing and monitoring system for heavy-duty CNC machine tools. This paper fills in the blank of this kind of review articles to guide the development of this industry field and opens up new areas of research on the heavy-duty CNC machine tool thermal error.

  12. Modal identification of spindle-tool unit in high-speed machining

    NASA Astrophysics Data System (ADS)

    Gagnol, Vincent; Le, Thien-Phu; Ray, Pascal

    2011-10-01

    The accurate knowledge of high-speed motorised spindle dynamic behaviour during machining is important in order to ensure the reliability of machine tools in service and the quality of machined parts. More specifically, the prediction of stable cutting regions, which is a critical requirement for high-speed milling operations, requires the accurate estimation of tool/holder/spindle set dynamic modal parameters. These estimations are generally obtained through Frequency Response Function (FRF) measurements of the non-rotating spindle. However, significant changes in modal parameters are expected to occur during operation, due to high-speed spindle rotation. The spindle's modal variations are highlighted through an integrated finite element model of the dynamic high-speed spindle-bearing system, taking into account rotor dynamics effects. The dependency of dynamic behaviour on speed range is then investigated and determined with accuracy. The objective of the proposed paper is to validate these numerical results through an experiment-based approach. Hence, an experimental setup is elaborated to measure rotating tool vibration during the machining operation in order to determine the spindle's modal frequency variation with respect to spindle speed in an industrial environment. The identification of natural frequencies of the spindle under rotating conditions is challenging, due to the low number of sensors and the presence of many harmonics in the measured signals. In order to overcome these issues and to extract the characteristics of the system, the spindle modes are determined through a 3-step procedure. First, spindle modes are highlighted using the Frequency Domain Decomposition (FDD) technique, with a new formulation at the considered rotating speed. These extracted modes are then analysed through the value of their respective damping ratios in order to separate the harmonics component from structural spindle natural frequencies. Finally, the stochastic

  13. ATST telescope mount: telescope of machine tool

    NASA Astrophysics Data System (ADS)

    Jeffers, Paul; Stolz, Günter; Bonomi, Giovanni; Dreyer, Oliver; Kärcher, Hans

    2012-09-01

    The Advanced Technology Solar Telescope (ATST) will be the largest solar telescope in the world, and will be able to provide the sharpest views ever taken of the solar surface. The telescope has a 4m aperture primary mirror, however due to the off axis nature of the optical layout, the telescope mount has proportions similar to an 8 meter class telescope. The technology normally used in this class of telescope is well understood in the telescope community and has been successfully implemented in numerous projects. The world of large machine tools has developed in a separate realm with similar levels of performance requirement but different boundary conditions. In addition the competitive nature of private industry has encouraged development and usage of more cost effective solutions both in initial capital cost and thru-life operating cost. Telescope mounts move relatively slowly with requirements for high stability under external environmental influences such as wind buffeting. Large machine tools operate under high speed requirements coupled with high application of force through the machine but with little or no external environmental influences. The benefits of these parallel development paths and the ATST system requirements are being combined in the ATST Telescope Mount Assembly (TMA). The process of balancing the system requirements with new technologies is based on the experience of the ATST project team, Ingersoll Machine Tools who are the main contractor for the TMA and MT Mechatronics who are their design subcontractors. This paper highlights a number of these proven technologies from the commercially driven machine tool world that are being introduced to the TMA design. Also the challenges of integrating and ensuring that the differences in application requirements are accounted for in the design are discussed.

  14. USSR Report, Machine Tools and Metalworking Equipment, No. 6

    DTIC Science & Technology

    1983-05-18

    production output per machine tool at a tool plant average 2-3 times the figures for tool shops. This is explained by the well-known advantages of...specialized production. Specifically, the advantages of standardization and unification of machine- attachment design can be fully exploited in...lemiiiiä IS MVCti\\e UtiUzation °f appropriate special equipmeT ters)! million thread-cutting dies, and 2.3 million milling cut- The advantages of

  15. PCD tool wear and its monitoring in machining tungsten

    NASA Astrophysics Data System (ADS)

    Wang, Lijiang; Zhang, Zhenlie; Sun, Qi; Liu, Pin

    The views of Chinese and foreign researchers are quite different as to whether or not polycrystalline diamond (PCD) tools can machine tungsten that is used in the aerospace and electronic industries. A study is presented that shows the possibility of machining tungsten, and a new method is developed for monitoring the tool wear in production.

  16. Visualization tool for human-machine interface designers

    NASA Astrophysics Data System (ADS)

    Prevost, Michael P.; Banda, Carolyn P.

    1991-06-01

    As modern human-machine systems continue to grow in capabilities and complexity, system operators are faced with integrating and managing increased quantities of information. Since many information components are highly related to each other, optimizing the spatial and temporal aspects of presenting information to the operator has become a formidable task for the human-machine interface (HMI) designer. The authors describe a tool in an early stage of development, the Information Source Layout Editor (ISLE). This tool is to be used for information presentation design and analysis; it uses human factors guidelines to assist the HMI designer in the spatial layout of the information required by machine operators to perform their tasks effectively. These human factors guidelines address such areas as the functional and physical relatedness of information sources. By representing these relationships with metaphors such as spring tension, attractors, and repellers, the tool can help designers visualize the complex constraint space and interacting effects of moving displays to various alternate locations. The tool contains techniques for visualizing the relative 'goodness' of a configuration, as well as mechanisms such as optimization vectors to provide guidance toward a more optimal design. Also available is a rule-based design checker to determine compliance with selected human factors guidelines.

  17. Method for producing hard-surfaced tools and machine components

    DOEpatents

    McHargue, Carl J.

    1985-01-01

    In one aspect, the invention comprises a method for producing tools and machine components having superhard crystalline-ceramic work surfaces. Broadly, the method comprises two steps: A tool or machine component having a ceramic near-surface region is mounted in ion-implantation apparatus. The region then is implanted with metal ions to form, in the region, a metastable alloy of the ions and said ceramic. The region containing the alloy is characterized by a significant increase in hardness properties, such as microhardness, fracture-toughness, and/or scratch-resistance. The resulting improved article has good thermal stability at temperatures characteristic of typical tool and machine-component uses. The method is relatively simple and reproducible.

  18. Method for producing hard-surfaced tools and machine components

    DOEpatents

    McHargue, C.J.

    1981-10-21

    In one aspect, the invention comprises a method for producing tools and machine components having superhard crystalline-ceramic work surfaces. Broadly, the method comprises two steps: a tool or machine component having a ceramic near-surface region is mounted in ion-implantation apparatus. The region then is implanted with metal ions to form, in the region, a metastable alloy of the ions and said ceramic. The region containing the alloy is characterized by a significant increase in hardness properties, such as microhardness, fracture-toughness, and/or scratch-resistance. The resulting improved article has good thermal stability at temperatures characteristic of typical tool and machine-component uses. The method is relatively simple and reproducible.

  19. Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

    NASA Astrophysics Data System (ADS)

    Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

    2018-03-01

    The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

  20. An iterative learning control method with application for CNC machine tools

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kim, D.I.; Kim, S.

    1996-01-01

    A proportional, integral, and derivative (PID) type iterative learning controller is proposed for precise tracking control of industrial robots and computer numerical controller (CNC) machine tools performing repetitive tasks. The convergence of the output error by the proposed learning controller is guaranteed under a certain condition even when the system parameters are not known exactly and unknown external disturbances exist. As the proposed learning controller is repeatedly applied to the industrial robot or the CNC machine tool with the path-dependent repetitive task, the distance difference between the desired path and the actual tracked or machined path, which is one ofmore » the most significant factors in the evaluation of control performance, is progressively reduced. The experimental results demonstrate that the proposed learning controller can improve machining accuracy when the CNC machine tool performs repetitive machining tasks.« less

  1. Method and apparatus for characterizing and enhancing the functional performance of machine tools

    DOEpatents

    Barkman, William E; Babelay, Jr., Edwin F; Smith, Kevin Scott; Assaid, Thomas S; McFarland, Justin T; Tursky, David A; Woody, Bethany; Adams, David

    2013-04-30

    Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include workpiece surface finish, and the ability to generate chips of the desired length.

  2. Tool feed influence on the machinability of CO(2) laser optics.

    PubMed

    Arnold, J B; Steger, P J; Saito, T T

    1975-08-01

    Influence of tool feed on reflectivity of diamond-machined surfaces was evaluated using materials (gold, silver, and copper) from which CO(2) laser optics are primarily produced. Fifteen specimens were machined by holding all machining parameters constant, except tool feed. Tool feed was allowed to vary by controlled amounts from one evaluation zone (or part) to another. Past experience has verified that the quality of a diamond-machined surface is not a function of the cutting velocity; therefore, this experiment was conducted on the basis that a variation in cutting velocity was not an influencing factor on the diamondturning process. Inspection results of the specimens indicated that tool feeds significantly higher than 5.1 micro/rev (200 microin./rev) produced detrimental effects on the machined surfaces. In some cases, at feeds as high as 13 microm/rev (500 microin./rev), visible scoring was evident. Those surfaces produced with tool feeds less than 5.1 microm/rev had little difference in reflectivity. Measurements indicat d that their reflectivity existed in a range from 96.7% to 99.3% at 10.6 microm.

  3. Machine Tool Operation, Course Description.

    ERIC Educational Resources Information Center

    Denny, Walter E.; Anderson, Floyd L.

    Prepared by an instructor and curriculum specialists, this course of study was designed to meet the individual needs of the dropout and/or hard-core unemployed youth by providing them skill training, related information, and supportive services knowledge in machine tool operation. The achievement level of each student is determined at entry, and…

  4. Mississippi Curriculum Framework for Machine Tool Operation/Machine Shop (Program CIP: 48.0503--Machine Shop Assistant). Secondary Programs.

    ERIC Educational Resources Information Center

    Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

    This document, which reflects Mississippi's statutory requirement that instructional programs be based on core curricula and performance-based assessment, contains outlines of the instructional units required in local instructional management plans and daily lesson plans for machine tool operation/machine shop I and II. Presented first are a…

  5. Surface structuring of boron doped CVD diamond by micro electrical discharge machining

    NASA Astrophysics Data System (ADS)

    Schubert, A.; Berger, T.; Martin, A.; Hackert-Oschätzchen, M.; Treffkorn, N.; Kühn, R.

    2018-05-01

    Boron doped diamond materials, which are generated by Chemical Vapor Deposition (CVD), offer a great potential for the application on highly stressed tools, e. g. in cutting or forming processes. As a result of the CVD process rough surfaces arise, which require a finishing treatment in particular for the application in forming tools. Cutting techniques such as milling and grinding are hardly applicable for the finish machining because of the high strength of diamond. Due to its process principle of ablating material by melting and evaporating, Electrical Discharge Machining (EDM) is independent of hardness, brittleness or toughness of the workpiece material. EDM is a suitable technology for machining and structuring CVD diamond, since boron doped CVD diamond is electrically conductive. In this study the ablation characteristics of boron doped CVD diamond by micro electrical discharge machining are investigated. Experiments were carried out to investigate the influence of different process parameters on the machining result. The impact of tool-polarity, voltage and discharge energy on the resulting erosion geometry and the tool wear was analyzed. A variation in path overlapping during the erosion of planar areas leads to different microstructures. The results show that micro EDM is a suitable technology for finishing of boron doped CVD diamond.

  6. The in-situ 3D measurement system combined with CNC machine tools

    NASA Astrophysics Data System (ADS)

    Zhao, Huijie; Jiang, Hongzhi; Li, Xudong; Sui, Shaochun; Tang, Limin; Liang, Xiaoyue; Diao, Xiaochun; Dai, Jiliang

    2013-06-01

    With the development of manufacturing industry, the in-situ 3D measurement for the machining workpieces in CNC machine tools is regarded as the new trend of efficient measurement. We introduce a 3D measurement system based on the stereovision and phase-shifting method combined with CNC machine tools, which can measure 3D profile of the machining workpieces between the key machining processes. The measurement system utilizes the method of high dynamic range fringe acquisition to solve the problem of saturation induced by specular lights reflected from shiny surfaces such as aluminum alloy workpiece or titanium alloy workpiece. We measured two workpieces of aluminum alloy on the CNC machine tools to demonstrate the effectiveness of the developed measurement system.

  7. A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes.

    PubMed

    Vogl, Gregory W; Weiss, Brian A; Donmez, M Alkan

    2015-01-01

    A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a 'sensor box' to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality.

  8. Effects of machining parameters on tool life and its optimization in turning mild steel with brazed carbide cutting tool

    NASA Astrophysics Data System (ADS)

    Dasgupta, S.; Mukherjee, S.

    2016-09-01

    One of the most significant factors in metal cutting is tool life. In this research work, the effects of machining parameters on tool under wet machining environment were studied. Tool life characteristics of brazed carbide cutting tool machined against mild steel and optimization of machining parameters based on Taguchi design of experiments were examined. The experiments were conducted using three factors, spindle speed, feed rate and depth of cut each having three levels. Nine experiments were performed on a high speed semi-automatic precision central lathe. ANOVA was used to determine the level of importance of the machining parameters on tool life. The optimum machining parameter combination was obtained by the analysis of S/N ratio. A mathematical model based on multiple regression analysis was developed to predict the tool life. Taguchi's orthogonal array analysis revealed the optimal combination of parameters at lower levels of spindle speed, feed rate and depth of cut which are 550 rpm, 0.2 mm/rev and 0.5mm respectively. The Main Effects plot reiterated the same. The variation of tool life with different process parameters has been plotted. Feed rate has the most significant effect on tool life followed by spindle speed and depth of cut.

  9. A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes

    PubMed Central

    Vogl, Gregory W.; Weiss, Brian A.; Donmez, M. Alkan

    2017-01-01

    A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a ‘sensor box’ to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality. PMID:28691039

  10. Tooling Foam for Structural Composite Applications

    NASA Technical Reports Server (NTRS)

    DeLay, Tom; Smith, Brett H.; Ely, Kevin; MacArthur, Doug

    1998-01-01

    Tooling technology applications for composite structures fabrication have been expanded at MSFC's Productivity Enhancement Complex (PEC). Engineers from NASA/MSFC and Lockheed Martin Corporation have developed a tooling foam for use in composite materials processing and manufacturing that exhibits superior thermal and mechanical properties in comparison with other tooling foam materials. This tooling foam is also compatible with most preimpregnated composite resins such as epoxy, bismaleimide, phenolic and their associated cure cycles. MARCORE tooling foam has excellent processability for applications requiring either integral or removable tooling. It can also be tailored to meet the requirements for composite processing of parts with unlimited cross sectional area. A shelf life of at least six months is easily maintained when components are stored between 50F - 70F. The MARCORE tooling foam system is a two component urethane-modified polyisocyanurate, high density rigid foam with zero ozone depletion potential. This readily machineable, lightweight tooling foam is ideal for composite structures fabrication and is dimensionally stable at temperatures up to 350F and pressures of 100 psi.

  11. Smart Cutting Tools and Smart Machining: Development Approaches, and Their Implementation and Application Perspectives

    NASA Astrophysics Data System (ADS)

    Cheng, Kai; Niu, Zhi-Chao; Wang, Robin C.; Rakowski, Richard; Bateman, Richard

    2017-09-01

    Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing technologies in line with the advance of Industry 4.0 concepts. This paper presents some innovative design concepts and, in particular, the development of four types of smart cutting tools, including a force-based smart cutting tool, a temperature-based internally-cooled cutting tool, a fast tool servo (FTS) and smart collets for ultraprecision and micro manufacturing purposes. Implementation and application perspectives of these smart cutting tools are explored and discussed particularly for smart machining against a number of industrial application requirements. They are contamination-free machining, machining of tool-wear-prone Si-based infra-red devices and medical applications, high speed micro milling and micro drilling, etc. Furthermore, implementation techniques are presented focusing on: (a) plug-and-produce design principle and the associated smart control algorithms, (b) piezoelectric film and surface acoustic wave transducers to measure cutting forces in process, (c) critical cutting temperature control in real-time machining, (d) in-process calibration through machining trials, (e) FE-based design and analysis of smart cutting tools, and (f) application exemplars on adaptive smart machining.

  12. Tool simplifies machining of pipe ends for precision welding

    NASA Technical Reports Server (NTRS)

    Matus, S. T.

    1969-01-01

    Single tool prepares a pipe end for precision welding by simultaneously performing internal machining, end facing, and bevel cutting to specification standards. The machining operation requires only one milling adjustment, can be performed quickly, and produces the high quality pipe-end configurations required to ensure precision-welded joints.

  13. Calibrated thermal microscopy of the tool-chip interface in machining

    NASA Astrophysics Data System (ADS)

    Yoon, Howard W.; Davies, Matthew A.; Burns, Timothy J.; Kennedy, M. D.

    2000-03-01

    A critical parameter in predicting tool wear during machining and in accurate computer simulations of machining is the spatially-resolved temperature at the tool-chip interface. We describe the development and the calibration of a nearly diffraction-limited thermal-imaging microscope to measure the spatially-resolved temperatures during the machining of an AISI 1045 steel with a tungsten-carbide tool bit. The microscope has a target area of 0.5 mm X 0.5 mm square region with a < 5 micrometers spatial resolution and is based on a commercial InSb 128 X 128 focal plane array with an all reflective microscope objective. The minimum frame image acquisition time is < 1 ms. The microscope is calibrated using a standard blackbody source from the radiance temperature calibration laboratory at the National Institute of Standards and Technology, and the emissivity of the machined material is deduced from the infrared reflectivity measurements. The steady-state thermal images from the machining of 1045 steel are compared to previous determinations of tool temperatures from micro-hardness measurements and are found to be in agreement with those studies. The measured average chip temperatures are also in agreement with the temperature rise estimated from energy balance considerations. From these calculations and the agreement between the experimental and the calculated determinations of the emissivity of the 1045 steel, the standard uncertainty of the temperature measurements is estimated to be about 45 degree(s)C at 900 degree(s)C.

  14. Estimation of tool wear compensation during micro-electro-discharge machining of silicon using process simulation

    NASA Astrophysics Data System (ADS)

    Muralidhara, .; Vasa, Nilesh J.; Singaperumal, M.

    2010-02-01

    A micro-electro-discharge machine (Micro EDM) was developed incorporating a piezoactuated direct drive tool feed mechanism for micromachining of Silicon using a copper tool. Tool and workpiece materials are removed during Micro EDM process which demand for a tool wear compensation technique to reach the specified depth of machining on the workpiece. An in-situ axial tool wear and machining depth measurement system is developed to investigate axial wear ratio variations with machining depth. Stepwise micromachining experiments on silicon wafer were performed to investigate the variations in the silicon removal and tool wear depths with increase in tool feed. Based on these experimental data, a tool wear compensation method is proposed to reach the desired depth of micromachining on silicon using copper tool. Micromachining experiments are performed with the proposed tool wear compensation method and a maximum workpiece machining depth variation of 6% was observed.

  15. A defect-driven diagnostic method for machine tool spindles

    PubMed Central

    Vogl, Gregory W.; Donmez, M. Alkan

    2016-01-01

    Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition. PMID:28065985

  16. The U.S. Machine Tool Industry and the Defense Industrial Base

    DTIC Science & Technology

    1983-01-01

    GOLD, Director, Research Program in Industrial Economics , Case Western Reserve University HAMILTON HERMAN, Management Consultant NATHANIEL S. HOWE...Traditional U.S. Machine Tool Industry ........ 8 Technological Trends Shaping the Industry ........ 18 Economic Trends .................................. 23...sustained economic recovery and aggressive steps by both government and industry, an effectively com- petitive domestic machine tool industry can emerge

  17. Machine and Woodworking Tool Safety. Module SH-24. Safety and Health.

    ERIC Educational Resources Information Center

    Center for Occupational Research and Development, Inc., Waco, TX.

    This student module on machine and woodworking tool safety is one of 50 modules concerned with job safety and health. This module discusses specific practices and precautions concerned with the efficient operation and use of most machine and woodworking tools in use today. Following the introduction, 13 objectives (each keyed to a page in the…

  18. Classifying Structures in the ISM with Machine Learning Techniques

    NASA Astrophysics Data System (ADS)

    Beaumont, Christopher; Goodman, A. A.; Williams, J. P.

    2011-01-01

    The processes which govern molecular cloud evolution and star formation often sculpt structures in the ISM: filaments, pillars, shells, outflows, etc. Because of their morphological complexity, these objects are often identified manually. Manual classification has several disadvantages; the process is subjective, not easily reproducible, and does not scale well to handle increasingly large datasets. We have explored to what extent machine learning algorithms can be trained to autonomously identify specific morphological features in molecular cloud datasets. We show that the Support Vector Machine algorithm can successfully locate filaments and outflows blended with other emission structures. When the objects of interest are morphologically distinct from the surrounding emission, this autonomous classification achieves >90% accuracy. We have developed a set of IDL-based tools to apply this technique to other datasets.

  19. Optimizing the way kinematical feed chains with great distance between slides are chosen for CNC machine tools

    NASA Astrophysics Data System (ADS)

    Lucian, P.; Gheorghe, S.

    2017-08-01

    This paper presents a new method, based on FRISCO formula, for optimizing the choice of the best control system for kinematical feed chains with great distance between slides used in computer numerical controlled machine tools. Such machines are usually, but not limited to, used for machining large and complex parts (mostly in the aviation industry) or complex casting molds. For such machine tools the kinematic feed chains are arranged in a dual-parallel drive structure that allows the mobile element to be moved by the two kinematical branches and their related control systems. Such an arrangement allows for high speed and high rigidity (a critical requirement for precision machining) during the machining process. A significant issue for such an arrangement it’s the ability of the two parallel control systems to follow the same trajectory accurately in order to address this issue it is necessary to achieve synchronous motion control for the two kinematical branches ensuring that the correct perpendicular position it’s kept by the mobile element during its motion on the two slides.

  20. Coupling for joining a ball nut to a machine tool carriage

    DOEpatents

    Gerth, Howard L.

    1979-01-01

    The present invention relates to an improved coupling for joining a lead screw ball nut to a machine tool carriage. The ball nut is coupled to the machine tool carriage by a plurality of laterally flexible bolts which function as hinges during the rotation of the lead screw for substantially reducing lateral carriage movement due to wobble in the lead screw.

  1. Novel tool wear monitoring method in milling difficult-to-machine materials using cutting chip formation

    NASA Astrophysics Data System (ADS)

    Zhang, P. P.; Guo, Y.; Wang, B.

    2017-05-01

    The main problems in milling difficult-to-machine materials are the high cutting temperature and rapid tool wear. However it is impossible to investigate tool wear in machining. Tool wear and cutting chip formation are two of the most important representations for machining efficiency and quality. The purpose of this paper is to develop the model of tool wear with cutting chip formation (width of chip and radian of chip) on difficult-to-machine materials. Thereby tool wear is monitored by cutting chip formation. A milling experiment on the machining centre with three sets cutting parameters was performed to obtain chip formation and tool wear. The experimental results show that tool wear increases gradually along with cutting process. In contrast, width of chip and radian of chip decrease. The model is developed by fitting the experimental data and formula transformations. The most of monitored errors of tool wear by the chip formation are less than 10%. The smallest error is 0.2%. Overall errors by the radian of chip are less than the ones by the width of chip. It is new way to monitor and detect tool wear by cutting chip formation in milling difficult-to-machine materials.

  2. Identification of Technological Parameters of Ni-Alloys When Machining by Monolithic Ceramic Milling Tool

    NASA Astrophysics Data System (ADS)

    Czán, Andrej; Kubala, Ondrej; Danis, Igor; Czánová, Tatiana; Holubják, Jozef; Mikloš, Matej

    2017-12-01

    The ever-increasing production and the usage of hard-to-machine progressive materials are the main cause of continual finding of new ways and methods of machining. One of these ways is the ceramic milling tool, which combines the pros of conventional ceramic cutting materials and pros of conventional coating steel-based insert. These properties allow to improve cutting conditions and so increase the productivity with preserved quality known from conventional tools usage. In this paper, there is made the identification of properties and possibilities of this tool when machining of hard-to-machine materials such as nickel alloys using in airplanes engines. This article is focused on the analysis and evaluation ordinary technological parameters and surface quality, mainly roughness of surface and quality of machined surface and tool wearing.

  3. Analysis of the application of poly-nanocrystalline diamond tools for ultra precision machining of steel with ultrasonic assistance

    NASA Astrophysics Data System (ADS)

    Doetz, M.; Dambon, O.; Klocke, F.; Bulla, B.; Schottka, K.; Robertson, D. J.

    2017-10-01

    Ultra-precision diamond turning enables the manufacturing of parts with mirror-like surfaces and highest form accuracies out of non-ferrous, a few crystalline and plastic materials. Furthermore, an ultrasonic assistance has the ability to push these boundaries and enables the machining of materials like steel, which is not possible in a conventional way due to the excessive tool wear caused by the affinity of carbon to iron. Usually monocrystalline diamonds tools are applied due to their unsurpassed cutting edge properties. New cutting tool material developments have shown that it is possible to produce tools made of nano-polycrystalline diamonds with cutting edges equivalent to monocrystalline diamonds. In nano-polycrystalline diamonds ultra-fine grains of a few tens of nanometers are firmly and directly bonded together creating an unisotropic structure. The properties of this material are described to be isotropic, harder and tougher than those of the monocrystalline diamonds, which are unisotropic. This publication will present machining results from the newest investigations of the process potential of this new polycrystalline cutting material. In order to provide a baseline with which to characterize the cutting material cutting experiments on different conventional machinable materials like Cooper or Aluminum are performed. The results provide information on the roughness and the topography of the surface focusing on the comparison to the results while machining with monocrystalline diamond. Furthermore, the cutting material is tested in machining steel with ultrasonic assistance with a focus on tool life time and surface roughness. An outlook on the machinability of other materials will be given.

  4. Robotic edge machining using elastic abrasive tool

    NASA Astrophysics Data System (ADS)

    Sidorova, A. V.; Semyonov, E. N.; Belomestnykh, A. S.

    2018-03-01

    The article describes a robotic center designed for automation of finishing operations, and analyzes technological aspects of an elastic abrasive tool applied for edge machining. Based on the experimental studies, practical recommendations on the application of the robotic center for finishing operations were developed.

  5. Machinability of Green Powder Metallurgy Components: Part I. Characterization of the Influence of Tool Wear

    NASA Astrophysics Data System (ADS)

    Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

    2007-06-01

    The green machining process is an interesting approach for solving the mediocre machining behavior of high-performance powder metallurgy (PM) steels. This process appears as a promising method for extending tool life and reducing machining costs. Recent improvements in binder/lubricant technologies have led to high green strength systems that enable green machining. So far, tool wear has been considered negligible when characterizing the machinability of green PM specimens. This inaccurate assumption may lead to the selection of suboptimum cutting conditions. The first part of this study involves the optimization of the machining parameters to minimize the effects of tool wear on the machinability in turning of green PM components. The second part of our work compares the sintered mechanical properties of components machined in green state with other machined after sintering.

  6. Diamond tool machining of materials which react with diamond

    DOEpatents

    Lundin, Ralph L.; Stewart, Delbert D.; Evans, Christopher J.

    1992-01-01

    Apparatus for the diamond machining of materials which detrimentally react with diamond cutting tools in which the cutting tool and the workpiece are chilled to very low temperatures. This chilling halts or retards the chemical reaction between the workpiece and the diamond cutting tool so that wear rates of the diamond tool on previously detrimental materials are comparable with the diamond turning of materials which do not react with diamond.

  7. A novel diamond micro-/nano-machining process for the generation of hierarchical micro-/nano-structures

    NASA Astrophysics Data System (ADS)

    Zhu, Zhiwei; To, Suet; Ehmann, Kornel F.; Xiao, Gaobo; Zhu, Wule

    2016-03-01

    A new mechanical micro-/nano-machining process that combines rotary spatial vibrations (RSV) of a diamond tool and the servo motions of the workpiece is proposed and applied for the generation of multi-tier hierarchical micro-/nano-structures. In the proposed micro-/nano-machining system, the servo motion, as the primary cutting motion generated by a slow-tool-servo, is adopted for the fine generation of the primary surfaces with complex shapes. The RSV, as the tertiary cutting operation, is superimposed on the secondary fundamental rotary cutting motion to construct secondary nano-structures on the primary surface. Since the RSV system generally works at much higher frequencies and motion resolution than the primary and secondary motions, it leads to an inherent hierarchical cutting architecture. To investigate the machining performance, complex micro-/nano-structures were generated and explored by both numerical simulations and actual cutting tests. Rotary vibrations of the diamond tool at a constant rotational distance offer an inherent constant cutting velocity, leading to the ability for the generation of homogeneous micro-/nano-structures with fixed amplitudes and frequencies of the vibrations, even over large-scale surfaces. Furthermore, by deliberately combining the non-resonant three-axial vibrations and the servo motion, the generation of a variety of micro-/nano-structures with complex shapes and with flexibly tunable feature sizes can be achieved.

  8. Department of Defense Tri-Service Precision Machine-Tool Program. Quarterly report, February--April 1978

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Not Available

    1978-06-01

    Following a planning period during which the Lawrence Livermore Laboratory and the Department of Defense managing sponsor, the USAF Materials Laboratory, agreed on work statements, the Department of Defense Tri-Service Precision Machine-Tool Program began in February 1978. Milestones scheduled for the first quarter have been met. Tasks and manpower requirements for two basic projects, precision-machining commercialization (PMC) and a machine-tool task force (MTTF), were defined. Progress by PMC includes: (1) documentation of existing precision machine-tool technology by initiation and compilation of a bibliography containing several hundred entries: (2) identification of the problems and needs of precision turning-machine builders and ofmore » precision turning-machine users interested in developing high-precision machining capability; and (3) organization of the schedule and content of the first seminar, to be held in October 1978, which will bring together representatives from the machine-tool and optics communities to address the problems and begin the process of high-precision machining commercialization. Progress by MTTF includes: (1) planning for the organization of a team effort of approximately 60 to 80 international experts to contribute in various ways to project objectives, namely, to summarize state-of-the-art cutting-machine-tool technology and to identify areas where future R and D should prove technically and economically profitable; (2) preparation of a comprehensive plan to achieve those objectives; and (3) preliminary arrangements for a plenary session, also in October, when the task force will meet to formalize the details for implementing the plan.« less

  9. Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

    NASA Astrophysics Data System (ADS)

    Okokpujie, Imhade Princess; Ikumapayi, Omolayo M.; Okonkwo, Ugochukwu C.; Salawu, Enesi Y.; Afolalu, Sunday A.; Dirisu, Joseph O.; Nwoke, Obinna N.; Ajayi, Oluseyi O.

    2017-12-01

    In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

  10. Machine tools error characterization and compensation by on-line measurement of artifact

    NASA Astrophysics Data System (ADS)

    Wahid Khan, Abdul; Chen, Wuyi; Wu, Lili

    2009-11-01

    Most manufacturing machine tools are utilized for mass production or batch production with high accuracy at a deterministic manufacturing principle. Volumetric accuracy of machine tools depends on the positional accuracy of the cutting tool, probe or end effector related to the workpiece in the workspace volume. In this research paper, a methodology is presented for volumetric calibration of machine tools by on-line measurement of an artifact or an object of a similar type. The machine tool geometric error characterization was carried out through a standard or an artifact, having similar geometry to the mass production or batch production product. The artifact was measured at an arbitrary position in the volumetric workspace with a calibrated Renishaw touch trigger probe system. Positional errors were stored into a computer for compensation purpose, to further run the manufacturing batch through compensated codes. This methodology was found quite effective to manufacture high precision components with more dimensional accuracy and reliability. Calibration by on-line measurement gives the advantage to improve the manufacturing process by use of deterministic manufacturing principle and found efficient and economical but limited to the workspace or envelop surface of the measured artifact's geometry or the profile.

  11. Tool path strategy and cutting process monitoring in intelligent machining

    NASA Astrophysics Data System (ADS)

    Chen, Ming; Wang, Chengdong; An, Qinglong; Ming, Weiwei

    2018-06-01

    Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.

  12. Diamond tool machining of materials which react with diamond

    DOEpatents

    Lundin, R.L.; Stewart, D.D.; Evans, C.J.

    1992-04-14

    An apparatus is described for the diamond machining of materials which detrimentally react with diamond cutting tools in which the cutting tool and the workpiece are chilled to very low temperatures. This chilling halts or retards the chemical reaction between the workpiece and the diamond cutting tool so that wear rates of the diamond tool on previously detrimental materials are comparable with the diamond turning of materials which do not react with diamond. 1 figs.

  13. Interpolator for numerically controlled machine tools

    DOEpatents

    Bowers, Gary L.; Davenport, Clyde M.; Stephens, Albert E.

    1976-01-01

    A digital differential analyzer circuit is provided that depending on the embodiment chosen can carry out linear, parabolic, circular or cubic interpolation. In the embodiment for parabolic interpolations, the circuit provides pulse trains for the X and Y slide motors of a two-axis machine to effect tool motion along a parabolic path. The pulse trains are generated by the circuit in such a way that parabolic tool motion is obtained from information contained in only one block of binary input data. A part contour may be approximated by one or more parabolic arcs. Acceleration and initial velocity values from a data block are set in fixed bit size registers for each axis separately but simultaneously and the values are integrated to obtain the movement along the respective axis as a function of time. Integration is performed by continual addition at a specified rate of an integrand value stored in one register to the remainder temporarily stored in another identical size register. Overflows from the addition process are indicative of the integral. The overflow output pulses from the second integration may be applied to motors which position the respective machine slides according to a parabolic motion in time to produce a parabolic machine tool motion in space. An additional register for each axis is provided in the circuit to allow "floating" of the radix points of the integrand registers and the velocity increment to improve position accuracy and to reduce errors encountered when the acceleration integrand magnitudes are small when compared to the velocity integrands. A divider circuit is provided in the output of the circuit to smooth the output pulse spacing and prevent motor stall, because the overflow pulses produced in the binary addition process are spaced unevenly in time. The divider has the effect of passing only every nth motor drive pulse, with n being specifiable. The circuit inputs (integrands, rates, etc.) are scaled to give exactly n times the

  14. Spindle Thermal Error Optimization Modeling of a Five-axis Machine Tool

    NASA Astrophysics Data System (ADS)

    Guo, Qianjian; Fan, Shuo; Xu, Rufeng; Cheng, Xiang; Zhao, Guoyong; Yang, Jianguo

    2017-05-01

    Aiming at the problem of low machining accuracy and uncontrollable thermal errors of NC machine tools, spindle thermal error measurement, modeling and compensation of a two turntable five-axis machine tool are researched. Measurement experiment of heat sources and thermal errors are carried out, and GRA(grey relational analysis) method is introduced into the selection of temperature variables used for thermal error modeling. In order to analyze the influence of different heat sources on spindle thermal errors, an ANN (artificial neural network) model is presented, and ABC(artificial bee colony) algorithm is introduced to train the link weights of ANN, a new ABC-NN(Artificial bee colony-based neural network) modeling method is proposed and used in the prediction of spindle thermal errors. In order to test the prediction performance of ABC-NN model, an experiment system is developed, the prediction results of LSR (least squares regression), ANN and ABC-NN are compared with the measurement results of spindle thermal errors. Experiment results show that the prediction accuracy of ABC-NN model is higher than LSR and ANN, and the residual error is smaller than 3 μm, the new modeling method is feasible. The proposed research provides instruction to compensate thermal errors and improve machining accuracy of NC machine tools.

  15. Lathe tool bit and holder for machining fiberglass materials

    NASA Technical Reports Server (NTRS)

    Winn, L. E. (Inventor)

    1972-01-01

    A lathe tool and holder combination for machining resin impregnated fiberglass cloth laminates is described. The tool holder and tool bit combination is designed to accommodate a conventional carbide-tipped, round shank router bit as the cutting medium, and provides an infinite number of cutting angles in order to produce a true and smooth surface in the fiberglass material workpiece with every pass of the tool bit. The technique utilizes damaged router bits which ordinarily would be discarded.

  16. 76 FR 27668 - ASC Machine Tools, Inc., Spokane Valley, WA; Notice of Negative Determination on Reconsideration

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-12

    ... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-72,971] ASC Machine Tools, Inc... workers and former workers of ASC Machine Tools, Inc., Spokane Valley, Washington (the subject firm). The... workers of ASC Machine Tools, Inc., Spokane Valley, Washington. Signed in Washington, DC, on this 2nd day...

  17. Machine Learning: A Crucial Tool for Sensor Design

    PubMed Central

    Zhao, Weixiang; Bhushan, Abhinav; Santamaria, Anthony D.; Simon, Melinda G.; Davis, Cristina E.

    2009-01-01

    Sensors have been widely used for disease diagnosis, environmental quality monitoring, food quality control, industrial process analysis and control, and other related fields. As a key tool for sensor data analysis, machine learning is becoming a core part of novel sensor design. Dividing a complete machine learning process into three steps: data pre-treatment, feature extraction and dimension reduction, and system modeling, this paper provides a review of the methods that are widely used for each step. For each method, the principles and the key issues that affect modeling results are discussed. After reviewing the potential problems in machine learning processes, this paper gives a summary of current algorithms in this field and provides some feasible directions for future studies. PMID:20191110

  18. Repurposing mainstream CNC machine tools for laser-based additive manufacturing

    NASA Astrophysics Data System (ADS)

    Jones, Jason B.

    2016-04-01

    The advent of laser technology has been a key enabler for industrial 3D printing, known as Additive Manufacturing (AM). Despite its commercial success and unique technical capabilities, laser-based AM systems are not yet able to produce parts with the same accuracy and surface finish as CNC machining. To enable the geometry and material freedoms afforded by AM, yet achieve the precision and productivity of CNC machining, hybrid combinations of these two processes have started to gain traction. To achieve the benefits of combined processing, laser technology has been integrated into mainstream CNC machines - effectively repurposing them as hybrid manufacturing platforms. This paper reviews how this engineering challenge has prompted beam delivery innovations to allow automated changeover between laser processing and machining, using standard CNC tool changers. Handling laser-processing heads using the tool changer also enables automated change over between different types of laser processing heads, further expanding the breadth of laser processing flexibility in a hybrid CNC. This paper highlights the development, challenges and future impact of hybrid CNCs on laser processing.

  19. Investigation of tool wear and surface roughness on machining of titanium alloy with MT-CVD cutting tool

    NASA Astrophysics Data System (ADS)

    Maity, Kalipada; Pradhan, Swastik

    2018-04-01

    In this study, machining of titanium alloy (grade 5) is carried out using MT-CVD coated cutting tool. Titanium alloys possess superior strength-to-weight ratio with good corrosion resistance. Most of the industries used titanium alloy for the manufacturing of various types of lightweight components. The parts made from Ti-6Al-4V largely used in aerospace, biomedical, automotive and marine sectors. The conventional machining of this material is very difficult, due to low thermal conductivity and high chemical reactivity properties. To achieve a good surface finish with minimum tool wear of cutting tool, the machining is carried out using MT-CVD coated cutting tool. The experiment is carried out using of Taguchi L27 array layout with three cutting variables and levels. To find out the optimum parametric setting desirability function analysis (DFA) approach is used. The analysis of variance is studied to know the percentage contribution of each cutting variables. The optimum parametric setting results calculated from DFA were validated through the confirmation test.

  20. 12. TOOL ROOM SHOWING LANDIS MACHINE CO. BOL/T THREADER (L), ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    12. TOOL ROOM SHOWING LANDIS MACHINE CO. BOL/T THREADER (L), OSTER MANUFACTURING CO. PIPE MASTER (R), AND OLDMAN KINK, A SHOP-MADE WELDING STRENGTH TESTER (L, BACKGROUND). VIEW NORTHEAST - Oldman Boiler Works, Office/Machine Shop, 32 Illinois Street, Buffalo, Erie County, NY

  1. New tool holder design for cryogenic machining of Ti6Al4V

    NASA Astrophysics Data System (ADS)

    Bellin, Marco; Sartori, Stefano; Ghiotti, Andrea; Bruschi, Stefania

    2017-10-01

    The renewed demand of increasing the machinability of the Ti6Al4V titanium alloy to produce biomedical and aerospace parts working at high temperature has recently led to the application of low-temperature coolants instead of conventional cutting fluids to increase both the tool life and the machined surface integrity. In particular, the liquid nitrogen directed to the tool rake face has shown a great capability of reducing the temperature at the chip-tool interface, as well as the chemical interaction between the tool coating and the titanium to be machined, therefore limiting the tool crater wear, and improving, at the same time, the chip breakability. Furthermore, the nitrogen is a safe, non-harmful, non-corrosive, odorless, recyclable, non-polluting and abundant gas, characteristics that further qualify it as an environmental friendly coolant to be applied to machining processes. However, the behavior of the system composed by the tool and the tool holder, exposed to the cryogenics temperatures may represent a critical issue in order to obtain components within the required geometrical tolerances. On this basis, the paper aims at presenting the design of an innovative tool holder installed on a CNC lathe, which includes the cryogenic coolant provision system, and which is able to hinder the part possible distortions due to the liquid nitrogen adduction by stabilizing its dimensions through the use of heating cartridges and appropriate sensors to monitor the temperature evolution of the tool holder.

  2. 49 CFR 1242.28 - Roadway machines, small tools and supplies, and snow removal (accounts XX-19-36 to XX-19-38...

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 9 2011-10-01 2011-10-01 false Roadway machines, small tools and supplies, and snow removal (accounts XX-19-36 to XX-19-38, inclusive). 1242.28 Section 1242.28 Transportation Other... PASSENGER SERVICE FOR RAILROADS 1 Operating Expenses-Way and Structures § 1242.28 Roadway machines, small...

  3. Comparison between laser interferometric and calibrated artifacts for the geometric test of machine tools

    NASA Astrophysics Data System (ADS)

    Sousa, Andre R.; Schneider, Carlos A.

    2001-09-01

    A touch probe is used on a 3-axis vertical machine center to check against a hole plate, calibrated on a coordinate measuring machine (CMM). By comparing the results obtained from the machine tool and CMM, the main machine tool error components are measured, attesting the machine accuracy. The error values can b used also t update the error compensation table at the CNC, enhancing the machine accuracy. The method is easy to us, has a lower cost than classical test techniques, and preliminary results have shown that its uncertainty is comparable to well established techniques. In this paper the method is compared with the laser interferometric system, regarding reliability, cost and time efficiency.

  4. Three dimensional electron microscopy and in silico tools for macromolecular structure determination

    PubMed Central

    Borkotoky, Subhomoi; Meena, Chetan Kumar; Khan, Mohammad Wahab; Murali, Ayaluru

    2013-01-01

    Recently, structural biology witnessed a major tool - electron microscopy - in solving the structures of macromolecules in addition to the conventional techniques, X-ray crystallography and nuclear magnetic resonance (NMR). Three dimensional transmission electron microscopy (3DTEM) is one of the most sophisticated techniques for structure determination of molecular machines. Known to give the 3-dimensional structures in its native form with literally no upper limit on size of the macromolecule, this tool does not need the crystallization of the protein. Combining the 3DTEM data with in silico tools, one can have better refined structure of a desired complex. In this review we are discussing about the recent advancements in three dimensional electron microscopy and tools associated with it. PMID:27092033

  5. Selected aspects of microelectronics technology and applications: Numerically controlled machine tools. Technology trends series no. 2

    NASA Astrophysics Data System (ADS)

    Sigurdson, J.; Tagerud, J.

    1986-05-01

    A UNIDO publication about machine tools with automatic control discusses the following: (1) numerical control (NC) machine tool perspectives, definition of NC, flexible manufacturing systems, robots and their industrial application, research and development, and sensors; (2) experience in developing a capability in NC machine tools; (3) policy issues; (4) procedures for retrieval of relevant documentation from data bases. Diagrams, statistics, bibliography are included.

  6. AN EIGHT WEEK SEMINAR IN AN INTRODUCTION TO NUMERICAL CONTROL ON TWO- AND THREE-AXIS MACHINE TOOLS FOR VOCATIONAL AND TECHNICAL MACHINE TOOL INSTRUCTORS. FINAL REPORT.

    ERIC Educational Resources Information Center

    BOLDT, MILTON; POKORNY, HARRY

    THIRTY-THREE MACHINE SHOP INSTRUCTORS FROM 17 STATES PARTICIPATED IN AN 8-WEEK SEMINAR TO DEVELOP THE SKILLS AND KNOWLEDGE ESSENTIAL FOR TEACHING THE OPERATION OF NUMERICALLY CONTROLLED MACHINE TOOLS. THE SEMINAR WAS GIVEN FROM JUNE 20 TO AUGUST 12, 1966, WITH COLLEGE CREDIT AVAILABLE THROUGH STOUT STATE UNIVERSITY. THE PARTICIPANTS COMPLETED AN…

  7. Multidisciplinary Investigations Regarding the Wear of Machine Tools Operating Into the Soil

    NASA Astrophysics Data System (ADS)

    Cardei, P.; Vladutoiu, L. C.; Gheorghe, G.; Fechete, T. L. V.; Chisiu, G.

    2018-01-01

    The paper presents the results obtained by the authors in investigating the problem of wear of work organs of machines working in continuous interaction with the soil. The phenomenon of the interaction of the tools of agricultural machinery for ploughing, and the soil, is a complex of phenomena, one of the most difficult to model. Among the phenomena involved in this interaction, friction and wear (of many types) are the most important. We did not take into account the chemical wear, and by the wear caused by weather conditions. Research has focused on formulating a theory that has more than a descriptive character, for it be used for application purposes. For this we used classical theoretical models, mathematical models based on the theory of continuous bodies, theory of flow of fluids around the profiles, as well as other theories, approached or not, in an attempt to solve as satisfactorily the issue of the wear, for the tools of the agricultural machines for the tillage. We also sought to highlight the fact that wear is a phenomenon on a micro and macro-scale scale, and its generating causes must ultimately be related to observable effects, on the macro-structural scale.

  8. The influence of the focus position on laser machining and laser micro-structuring monocrystalline diamond surface

    NASA Astrophysics Data System (ADS)

    Wu, Mingtao; Guo, Bing; Zhao, Qingliang; Fan, Rongwei; Dong, Zhiwei; Yu, Xin

    2018-06-01

    Micro-structured surface on diamond is widely used in microelectronics, optical elements, MEMS and NEMS components, ultra-precision machining tools, etc. The efficient micro-structuring of diamond material is still a challenging task. In this article, the influence of the focus position on laser machining and laser micro-structuring monocrystalline diamond surface were researched. At the beginning, the ablation threshold and its incubation effect of monocrystalline diamond were determined and discussed. As the accumulated laser pulses ranged from 40 to 5000, the laser ablation threshold decreased from 1.48 J/cm2 to 0.97 J/cm2. Subsequently, the variation of the ablation width and ablation depth in laser machining were studied. With enough pulse energy, the ablation width mainly depended on the laser propagation attributes while the ablation depth was a complex function of the focus position. Raman analysis was used to detect the variation of the laser machined diamond surface after the laser machining experiments. Graphite formation was discovered on the machined diamond surface and graphitization was enhanced after the defocusing quantity exceeded 45 μm. At last, several micro-structured surfaces were successfully fabricated on diamond surface with the defined micro-structure patterns and structuring ratios just by adjusting the defocusing quantity. The experimental structuring ratio was consistent with the theoretical analysis.

  9. Energy Survey of Machine Tools: Separating Power Information of the Main Transmission System During Machining Process

    NASA Astrophysics Data System (ADS)

    Liu, Shuang; Liu, Fei; Hu, Shaohua; Yin, Zhenbiao

    The major power information of the main transmission system in machine tools (MTSMT) during machining process includes effective output power (i.e. cutting power), input power and power loss from the mechanical transmission system, and the main motor power loss. These information are easy to obtain in the lab but difficult to evaluate in a manufacturing process. To solve this problem, a separation method is proposed here to extract the MTSMT power information during machining process. In this method, the energy flow and the mathematical models of major power information of MTSMT during the machining process are set up first. Based on the mathematical models and the basic data tables obtained from experiments, the above mentioned power information during machining process can be separated just by measuring the real time total input power of the spindle motor. The operation program of this method is also given.

  10. Analysis and control on changeable wheel tool system of hybrid grinding and polishing machine tool for blade finishing

    NASA Astrophysics Data System (ADS)

    He, Qiuwei; Lv, Xingming; Wang, Xin; Qu, Xingtian; Zhao, Ji

    2017-01-01

    Blade is the key component in the energy power equipment of turbine, aircraft engines and so on. Researches on the process and equipment for blade finishing become one of important and difficult point. To control precisely tool system of developed hybrid grinding and polishing machine tool for blade finishing, the tool system with changeable wheel for belt polishing is analyzed in this paper. Firstly, the belt length and wrap angle of each wheel in different position of tension wheel swing angle in the process of changing wheel is analyzed. The reasonable belt length is calculated by using MATLAB, and relationships between wrap angle of each wheel and cylinder expansion amount of contact wheel are obtained. Then, the control system for changeable wheel tool structure is developed. Lastly, the surface roughness of blade finishing is verified by experiments. Theoretical analysis and experimental results show that reasonable belt length and wheel wrap angle can be obtained by proposed analysis method, the changeable wheel tool system can be controlled precisely, and the surface roughness of blade after grinding meets the design requirements.

  11. AFM surface imaging of AISI D2 tool steel machined by the EDM process

    NASA Astrophysics Data System (ADS)

    Guu, Y. H.

    2005-04-01

    The surface morphology, surface roughness and micro-crack of AISI D2 tool steel machined by the electrical discharge machining (EDM) process were analyzed by means of the atomic force microscopy (AFM) technique. Experimental results indicate that the surface texture after EDM is determined by the discharge energy during processing. An excellent machined finish can be obtained by setting the machine parameters at a low pulse energy. The surface roughness and the depth of the micro-cracks were proportional to the power input. Furthermore, the AFM application yielded information about the depth of the micro-cracks is particularly important in the post treatment of AISI D2 tool steel machined by EDM.

  12. Guide for machine tool task force members

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sutton, G.P.

    1978-09-01

    The purpose of the guide is to assist members of the Machine Tool Task Force (MTTF) in doing the job, preparing technical summary papers, and helping to achieve a uniform, high-quality output from this comprehensive study effort. It supplements the MTTF Plan (UCRL-52552) which contains other important information on the method of operation of MTTF that is related to the preparation of MTTF reports.

  13. 25. VIEW OF THE MACHINE TOOL LAYOUT IN ROOMS 244 ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    25. VIEW OF THE MACHINE TOOL LAYOUT IN ROOMS 244 AND 296. MACHINES WERE USED FOR STAINLESS STEEL FABRICATION (THE J-LINE). THE ORIGINAL DRAWING HAS BEEN ARCHIVED ON MICROFILM. THE DRAWING WAS REPRODUCED AT THE BEST QUALITY POSSIBLE. LETTERS AND NUMBERS IN THE CIRCLES INDICATE FOOTER AND/OR COLUMN LOCATIONS. - Rocky Flats Plant, General Manufacturing, Support, Records-Central Computing, Southern portion of Plant, Golden, Jefferson County, CO

  14. Automated Tape Laying Machine for Composite Structures.

    DTIC Science & Technology

    The invention comprises an automated tape laying machine, for laying tape on a composite structure. The tape laying machine has a tape laying head...neatly cut. The automated tape laying device utilizes narrow width tape to increase machine flexibility and reduce wastage.

  15. Machining of AISI D2 Tool Steel with Multiple Hole Electrodes by EDM Process

    NASA Astrophysics Data System (ADS)

    Prasad Prathipati, R.; Devuri, Venkateswarlu; Cheepu, Muralimohan; Gudimetla, Kondaiah; Uzwal Kiran, R.

    2018-03-01

    In recent years, with the increasing of technology the demand for machining processes is increasing for the newly developed materials. The conventional machining processes are not adequate to meet the accuracy of the machining of these materials. The non-conventional machining processes of electrical discharge machining is one of the most efficient machining processes is being widely used to machining of high accuracy products of various industries. The optimum selection of process parameters is very important in machining processes as that of an electrical discharge machining as they determine surface quality and dimensional precision of the obtained parts, even though time consumption rate is higher for machining of large dimension features. In this work, D2 high carbon and chromium tool steel has been machined using electrical discharge machining with the multiple hole electrode technique. The D2 steel has several applications such as forming dies, extrusion dies and thread rolling. But the machining of this tool steel is very hard because of it shard alloyed elements of V, Cr and Mo which enhance its strength and wear properties. However, the machining is possible by using electrical discharge machining process and the present study implemented a new technique to reduce the machining time using a multiple hole copper electrode. In this technique, while machining with multiple holes electrode, fin like projections are obtained, which can be removed easily by chipping. Then the finishing is done by using solid electrode. The machining time is reduced to around 50% while using multiple hole electrode technique for electrical discharge machining.

  16. Theoretical and experimental research on machine tool servo system for ultra-precision position compensation on CNC lathe

    NASA Astrophysics Data System (ADS)

    Ma, Zhichao; Hu, Leilei; Zhao, Hongwei; Wu, Boda; Peng, Zhenxing; Zhou, Xiaoqin; Zhang, Hongguo; Zhu, Shuai; Xing, Lifeng; Hu, Huang

    2010-08-01

    The theories and techniques for improving machining accuracy via position control of diamond tool's tip and raising resolution of cutting depth on precise CNC lathes have been extremely focused on. A new piezo-driven ultra-precision machine tool servo system is designed and tested to improve manufacturing accuracy of workpiece. The mathematical model of machine tool servo system is established and the finite element analysis is carried out on parallel plate flexure hinges. The output position of diamond tool's tip driven by the machine tool servo system is tested via a contact capacitive displacement sensor. Proportional, integral, derivative (PID) feedback is also implemented to accommodate and compensate dynamical change owing cutting forces as well as the inherent non-linearity factors of the piezoelectric stack during cutting process. By closed loop feedback controlling strategy, the tracking error is limited to 0.8 μm. Experimental results have shown the proposed machine tool servo system could provide a tool positioning resolution of 12 nm, which is much accurate than the inherent CNC resolution magnitude. The stepped shaft of aluminum specimen with a step increment of cutting depth of 1 μm is tested, and the obtained contour illustrates the displacement command output from controller is accurately and real-time reflected on the machined part.

  17. Research on criticality analysis method of CNC machine tools components under fault rate correlation

    NASA Astrophysics Data System (ADS)

    Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

    2018-02-01

    In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

  18. 75 FR 65516 - ASC Machine Tools, Inc., Spokane Valley, WA; Notice of Affirmative Determination Regarding...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-25

    ... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-72,971] ASC Machine Tools, Inc... workers and former workers of ASC Machine Tools, Inc., Spokane Valley, Washington (the subject firm). The... cut metal, including assembled equipment, component parts of equipment, and spare parts. The negative...

  19. The influence of machining condition and cutting tool wear on surface roughness of AISI 4340 steel

    NASA Astrophysics Data System (ADS)

    Natasha, A. R.; Ghani, J. A.; Che Haron, C. H.; Syarif, J.

    2018-01-01

    Sustainable machining by using cryogenic coolant as the cutting fluid has been proven to enhance some machining outputs. The main objective of the current work was to investigate the influence of machining conditions; dry and cryogenic, as well as the cutting tool wear on the machined surface roughness of AISI 4340 steel. The experimental tests were performed using chemical vapor deposition (CVD) coated carbide inserts. The value of machined surface roughness were measured at 3 cutting intervals; beginning, middle, and end of the cutting based on the readings of the tool flank wear. The results revealed that cryogenic turning had the greatest influence on surface roughness when machined at lower cutting speed and higher feed rate. Meanwhile, the cutting tool wear was also found to influence the surface roughness, either improving it or deteriorating it, based on the severity and the mechanism of the flank wear.

  20. Machine Tool Technology. Tutoring Strategies for Metal Workers.

    ERIC Educational Resources Information Center

    Anoka-Hennepin Technical Coll., Minneapolis, MN.

    This tutoring strategies course designed to prepare tutors in a machine tool technology program was developed during a project to retrain defense industry workers at risk of job loss or dislocation because of conversion of the defense industry. Course contents are as follows: why you are here; qualifications of a tutor; what's in it for tutors,…

  1. SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

    PubMed Central

    2014-01-01

    Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

  2. SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

    PubMed

    Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

    2014-04-28

    It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

  3. Critical Technology Assessment of Five Axis Simultaneous Control Machine Tools

    DTIC Science & Technology

    2009-07-01

    assessment, BIS specifically examined: • The application of Export Control Classification Numbers ( ECCN ) 2B001.b.2 and 2B001.c.2 controls and related...availability of certain five axis simultaneous control mills, mill/turns, and machining centers controlled by ECCN 2B001.b.2 (but not grinders controlled by... ECCN 2B001.c.2) exists to China and Taiwan, which both have an indigenous capability to produce five axis simultaneous control machine tools with

  4. AutoQSAR: an automated machine learning tool for best-practice quantitative structure-activity relationship modeling.

    PubMed

    Dixon, Steven L; Duan, Jianxin; Smith, Ethan; Von Bargen, Christopher D; Sherman, Woody; Repasky, Matthew P

    2016-10-01

    We introduce AutoQSAR, an automated machine-learning application to build, validate and deploy quantitative structure-activity relationship (QSAR) models. The process of descriptor generation, feature selection and the creation of a large number of QSAR models has been automated into a single workflow within AutoQSAR. The models are built using a variety of machine-learning methods, and each model is scored using a novel approach. Effectiveness of the method is demonstrated through comparison with literature QSAR models using identical datasets for six end points: protein-ligand binding affinity, solubility, blood-brain barrier permeability, carcinogenicity, mutagenicity and bioaccumulation in fish. AutoQSAR demonstrates similar or better predictive performance as compared with published results for four of the six endpoints while requiring minimal human time and expertise.

  5. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 13: Laser Machining, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  6. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 3: Machining, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  7. Achieving Small Structures in Thin NiTi Sheets for Medical Applications with Water Jet and Micro Machining: A Comparison

    NASA Astrophysics Data System (ADS)

    Frotscher, M.; Kahleyss, F.; Simon, T.; Biermann, D.; Eggeler, G.

    2011-07-01

    NiTi shape memory alloys (SMA) are used for a variety of applications including medical implants and tools as well as actuators, making use of their unique properties. However, due to the hardness and strength, in combination with the high elasticity of the material, the machining of components can be challenging. The most common machining techniques used today are laser cutting and electrical discharge machining (EDM). In this study, we report on the machining of small structures into binary NiTi sheets, applying alternative processing methods being well-established for other metallic materials. Our results indicate that water jet machining and micro milling can be used to machine delicate structures, even in very thin NiTi sheets. Further work is required to optimize the cut quality and the machining speed in order to increase the cost-effectiveness and to make both methods more competitive.

  8. Quantitative Evaluation of Heavy Duty Machine Tools Remanufacturing Based on Modified Catastrophe Progression Method

    NASA Astrophysics Data System (ADS)

    shunhe, Li; jianhua, Rao; lin, Gui; weimin, Zhang; degang, Liu

    2017-11-01

    The result of remanufacturing evaluation is the basis for judging whether the heavy duty machine tool can remanufacture in the EOL stage of the machine tool lifecycle management.The objectivity and accuracy of evaluation is the key to the evaluation method.In this paper, the catastrophe progression method is introduced into the quantitative evaluation of heavy duty machine tools’ remanufacturing,and the results are modified by the comprehensive adjustment method,which makes the evaluation results accord with the standard of human conventional thinking.Using the catastrophe progression method to establish the heavy duty machine tools’ quantitative evaluation model,to evaluate the retired TK6916 type CNC floor milling-boring machine’s remanufacturing.The evaluation process is simple,high quantification,the result is objective.

  9. Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

    NASA Astrophysics Data System (ADS)

    Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

    2018-03-01

    Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

  10. Toward transient finite element simulation of thermal deformation of machine tools in real-time

    NASA Astrophysics Data System (ADS)

    Naumann, Andreas; Ruprecht, Daniel; Wensch, Joerg

    2018-01-01

    Finite element models without simplifying assumptions can accurately describe the spatial and temporal distribution of heat in machine tools as well as the resulting deformation. In principle, this allows to correct for displacements of the Tool Centre Point and enables high precision manufacturing. However, the computational cost of FE models and restriction to generic algorithms in commercial tools like ANSYS prevents their operational use since simulations have to run faster than real-time. For the case where heat diffusion is slow compared to machine movement, we introduce a tailored implicit-explicit multi-rate time stepping method of higher order based on spectral deferred corrections. Using the open-source FEM library DUNE, we show that fully coupled simulations of the temperature field are possible in real-time for a machine consisting of a stock sliding up and down on rails attached to a stand.

  11. Reverse engineering of machine-tool settings with modified roll for spiral bevel pinions

    NASA Astrophysics Data System (ADS)

    Liu, Guanglei; Chang, Kai; Liu, Zeliang

    2013-05-01

    Although a great deal of research has been dedicated to the synthesis of spiral bevel gears, little related to reverse engineering can be found. An approach is proposed to reverse the machine-tool settings of the pinion of a spiral bevel gear drive on the basis of the blank and tooth surface data obtained by a coordinate measuring machine(CMM). Real tooth contact analysis(RTCA) is performed to preliminary ascertain the contact pattern, the motion curve, as well as the position of the mean contact point. And then the tangent to the contact path and the motion curve are interpolated in the sense of the least square method to extract the initial values of the bias angle and the higher order coefficients(HOC) in modified roll motion. A trial tooth surface is generated by machine-tool settings derived from the local synthesis relating to the initial meshing performances and modified roll motion. An optimization objective is formed which equals the tooth surface deviation between the real tooth surface and the trial tooth surface. The design variables are the parameters describing the meshing performances at the mean contact point in addition to the HOC. When the objective is optimized within an arbitrarily given convergence tolerance, the machine-tool settings together with the HOC are obtained. The proposed approach is verified by a spiral bevel pinion used in the accessory gear box of an aviation engine. The trial tooth surfaces approach to the real tooth surface on the whole in the example. The results show that the convergent tooth surface deviation for the concave side on the average is less than 0.5 μm, and is less than 1.3 μm for the convex side. The biggest tooth surface deviation is 6.7 μm which is located at the corner of the grid on the convex side. Those nodes with relative bigger tooth surface deviations are all located at the boundary of the grid. An approach is proposed to figure out the machine-tool settings of a spiral bevel pinion by way of reverse

  12. Structural health monitoring for bolt loosening via a non-invasive vibro-haptics human-machine cooperative interface

    NASA Astrophysics Data System (ADS)

    Pekedis, Mahmut; Mascerañas, David; Turan, Gursoy; Ercan, Emre; Farrar, Charles R.; Yildiz, Hasan

    2015-08-01

    For the last two decades, developments in damage detection algorithms have greatly increased the potential for autonomous decisions about structural health. However, we are still struggling to build autonomous tools that can match the ability of a human to detect and localize the quantity of damage in structures. Therefore, there is a growing interest in merging the computational and cognitive concepts to improve the solution of structural health monitoring (SHM). The main object of this research is to apply the human-machine cooperative approach on a tower structure to detect damage. The cooperation approach includes haptic tools to create an appropriate collaboration between SHM sensor networks, statistical compression techniques and humans. Damage simulation in the structure is conducted by releasing some of the bolt loads. Accelerometers are bonded to various locations of the tower members to acquire the dynamic response of the structure. The obtained accelerometer results are encoded in three different ways to represent them as a haptic stimulus for the human subjects. Then, the participants are subjected to each of these stimuli to detect the bolt loosened damage in the tower. Results obtained from the human-machine cooperation demonstrate that the human subjects were able to recognize the damage with an accuracy of 88 ± 20.21% and response time of 5.87 ± 2.33 s. As a result, it is concluded that the currently developed human-machine cooperation SHM may provide a useful framework to interact with abstract entities such as data from a sensor network.

  13. Measurement techniques for determining the static stiffness of foundations for machine tools

    NASA Astrophysics Data System (ADS)

    Myers, A.; Barrans, S. M.; Ford, D. G.

    2005-01-01

    The paper presents a novel technique for accurately measuring the static stiffness of a machine tool concrete foundation using various items of metrology equipment. The foundation was loaded in a number of different ways which simulated the erection of the machine, traversing of the axes and loading of the heaviest component. The results were compared with the stiffness tolerances specified for the foundation which were deemed necessary in order that the machine alignments could be achieved. This paper is a continuation of research previously published for a FEA of the foundation.

  14. Advancing Research in Second Language Writing through Computational Tools and Machine Learning Techniques: A Research Agenda

    ERIC Educational Resources Information Center

    Crossley, Scott A.

    2013-01-01

    This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

  15. High productivity machining of holes in Inconel 718 with SiAlON tools

    NASA Astrophysics Data System (ADS)

    Agirreurreta, Aitor Arruti; Pelegay, Jose Angel; Arrazola, Pedro Jose; Ørskov, Klaus Bonde

    2016-10-01

    Inconel 718 is often employed in aerospace engines and power generation turbines. Numerous researches have proven the enhanced productivity when turning with ceramic tools compared to carbide ones, however there is considerably less information with regard to milling. Moreover, no knowledge has been published about machining holes with this type of tools. Additional research on different machining techniques, like for instance circular ramping, is critical to expand the productivity improvements that ceramics can offer. In this a 3D model of the machining and a number of experiments with SiAlON round inserts have been carried out in order to evaluate the effect of the cutting speed and pitch on the tool wear and chip generation. The results of this analysis show that three different types of chips are generated and also that there are three potential wear zones. Top slice wear is identified as the most critical wear type followed by the notch wear as a secondary wear mechanism. Flank wear and adhesion are also found in most of the tests.

  16. Producibility and Serviceability of Kevlar-49 Structures Made on Hot Layup Tools

    DTIC Science & Technology

    1975-05-01

    changes for a typical airframe composite part and established improved machining practices for Kevlar-49. Some of the more signifi- cant conclusions...reverse side if necessary 8nd identify by block number) Composite Materials Inlet Fairing Helicopters Hot Layup Tools (HLT) Kevlar -49 20. ABSTRACT...CLASSlFlCATlON OF THIS PAGE(Whm Data Bnlorod) 0 Demonstrate the low cost aspects of using Hot Layup Tools (HLT) to fabricate composite structures. a

  17. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 9: Tool and Die, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  18. Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

    NASA Astrophysics Data System (ADS)

    Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

    2016-12-01

    This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

  19. MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development

    PubMed Central

    Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

    2015-01-01

    Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/. PMID:25928885

  20. Statistical Machine Learning for Structured and High Dimensional Data

    DTIC Science & Technology

    2014-09-17

    AFRL-OSR-VA-TR-2014-0234 STATISTICAL MACHINE LEARNING FOR STRUCTURED AND HIGH DIMENSIONAL DATA Larry Wasserman CARNEGIE MELLON UNIVERSITY Final...Re . 8-98) v Prescribed by ANSI Std. Z39.18 14-06-2014 Final Dec 2009 - Aug 2014 Statistical Machine Learning for Structured and High Dimensional...area of resource-constrained statistical estimation. machine learning , high-dimensional statistics U U U UU John Lafferty 773-702-3813 > Research under

  1. Determination of real machine-tool settings and minimization of real surface deviation by computerized inspection

    NASA Technical Reports Server (NTRS)

    Litvin, Faydor L.; Kuan, Chihping; Zhang, YI

    1991-01-01

    A numerical method is developed for the minimization of deviations of real tooth surfaces from the theoretical ones. The deviations are caused by errors of manufacturing, errors of installment of machine-tool settings and distortion of surfaces by heat-treatment. The deviations are determined by coordinate measurements of gear tooth surfaces. The minimization of deviations is based on the proper correction of initially applied machine-tool settings. The contents of accomplished research project cover the following topics: (1) Descriptions of the principle of coordinate measurements of gear tooth surfaces; (2) Deviation of theoretical tooth surfaces (with examples of surfaces of hypoid gears and references for spiral bevel gears); (3) Determination of the reference point and the grid; (4) Determination of the deviations of real tooth surfaces at the points of the grid; and (5) Determination of required corrections of machine-tool settings for minimization of deviations. The procedure for minimization of deviations is based on numerical solution of an overdetermined system of n linear equations in m unknowns (m much less than n ), where n is the number of points of measurements and m is the number of parameters of applied machine-tool settings to be corrected. The developed approach is illustrated with numerical examples.

  2. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

    PubMed

    Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

    2015-01-01

    Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

  3. Reverse engineering of wörner type drilling machine structure.

    NASA Astrophysics Data System (ADS)

    Wibowo, A.; Belly, I.; llhamsyah, R.; Indrawanto; Yuwana, Y.

    2018-03-01

    A product design needs to be modified based on the conditions of production facilities and existing resource capabilities without reducing the functional aspects of the product itself. This paper describes the reverse engineering process of the main structure of the wörner type drilling machine to obtain a machine structure design that can be made by resources with limited ability by using simple processes. Some structural, functional and the work mechanism analyzes have been performed to understand the function and role of each basic components. The process of dismantling of the drilling machine and measuring each of the basic components was performed to obtain sets of the geometry and size data of each component. The geometric model of each structure components and the machine assembly were built to facilitate the simulation process and machine performance analysis that refers to ISO standard of drilling machine. The tolerance stackup analysis also performed to determine the type and value of geometrical and dimensional tolerances, which could affect the ease of the components to be manufactured and assembled

  4. Impact resistance of materials for guards on cutting machine tools--requirements in future European safety standards.

    PubMed

    Mewes, D; Trapp, R P

    2000-01-01

    Guards on machine tools are meant to protect operators from injuries caused by tools, workpieces, and fragments hurled out of the machine's working zone. This article presents the impact resistance requirements, which guards according to European safety standards for machine tools must satisfy. Based upon these standards the impact resistance of different guard materials was determined using cylindrical steel projectiles. Polycarbonate proves to be a suitable material for vision panels because of its high energy absorption capacity. The impact resistance of 8-mm thick polycarbonate is roughly equal to that of a 3-mm thick steel sheet Fe P01. The limited ageing stability, however, makes it necessary to protect polycarbonate against cooling lubricants by means of additional panes on both sides.

  5. Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

    PubMed Central

    Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

    2018-01-01

    Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system. PMID:29473877

  6. Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module.

    PubMed

    Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

    2018-02-23

    Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system.

  7. Influence of export control policy on the competitiveness of machine tool producing organizations

    NASA Astrophysics Data System (ADS)

    Ahrstrom, Jeffrey D.

    The possible influence of export control policies on producers of export controlled machine tools is examined in this quantitative study. International market competitiveness theories hold that market controlling policies such as export control regulations may influence an organization's ability to compete (Burris, 2010). Differences in domestic application of export control policy on machine tool exports may impose throttling effects on the competitiveness of participating firms (Freedenberg, 2010). Commodity shipments from Japan, Germany, and the United States to the Russian market will be examined using descriptive statistics; gravity modeling of these specific markets provides a foundation for comparison to actual shipment data; and industry participant responses to a user developed survey will provide additional data for analysis using a Kruskal-Wallis one-way analysis of variance. There is scarce academic research data on the topic of export control effects within the machine tool industry. Research results may be of interest to industry leadership in market participation decisions, advocacy arguments, and strategic planning. Industry advocates and export policy decision makers could find data of interest in supporting positions for or against modifications of export control policies.

  8. Universal Tool Grinder Operator Instructor's Guide. Part of Single-Tool Skills Program Machine Industries Occupations.

    ERIC Educational Resources Information Center

    New York State Education Dept., Albany. Div. of Curriculum Development.

    The document is an instructor's guide for a course on universal tool grinder operation. The course is designed to train people in making complicated machine setups and precision in the grinding operations and, although intended primarily for adult learners, it can be adapted for high school use. The guide is divided into three parts: (1) the…

  9. Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

    NASA Astrophysics Data System (ADS)

    Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

    2017-12-01

    Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

  10. Machinability of nickel based alloys using electrical discharge machining process

    NASA Astrophysics Data System (ADS)

    Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

    2018-04-01

    The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

  11. Free-form machining for micro-imaging systems

    NASA Astrophysics Data System (ADS)

    Barkman, Michael L.; Dutterer, Brian S.; Davies, Matthew A.; Suleski, Thomas J.

    2008-02-01

    While mechanical ruling and single point diamond turning has been a mainstay of optical fabrication for many years, many types of micro-optical devices and structures are not conducive to simple diamond turning or ruling, such as, for example, microlens arrays, and optical surfaces with non-radial symmetry. More recent developments in machining technology have enabled significant expansion of fabrication capabilities. Modern machine tools can generate complex three-dimensional structures with optical quality surface finish, and fabricate structures across a dynamic range of dimensions not achievable with lithographic techniques. In particular, five-axis free-form micromachining offers a great deal of promise for realization of essentially arbitrary surface structures, including surfaces not realizable through binary or analog lithographic techniques. Furthermore, these machines can generate geometric features with optical finish on scales ranging from centimeters to micrometers with accuracies of 10s of nanometers. In this paper, we discuss techniques and applications of free-form surface machining of micro-optical elements. Aspects of diamond machine tool design to realize desired surface geometries in specific materials are discussed. Examples are presented, including fabrication of aspheric lens arrays in germanium for compact infrared imaging systems. Using special custom kinematic mounting equipment and the additional axes of the machine, the lenses were turned with surface finish better than 2 nm RMS and center to center positioning accuracy of +/-0.5 μm.

  12. Prediction Of Abrasive And Diffusive Tool Wear Mechanisms In Machining

    NASA Astrophysics Data System (ADS)

    Rizzuti, S.; Umbrello, D.

    2011-01-01

    Tool wear prediction is regarded as very important task in order to maximize tool performance, minimize cutting costs and improve the quality of workpiece in cutting. In this research work, an experimental campaign was carried out at the varying of cutting conditions with the aim to measure both crater and flank tool wear, during machining of an AISI 1045 with an uncoated carbide tool P40. Parallel a FEM-based analysis was developed in order to study the tool wear mechanisms, taking also into account the influence of the cutting conditions and the temperature reached on the tool surfaces. The results show that, when the temperature of the tool rake surface is lower than the activation temperature of the diffusive phenomenon, the wear rate can be estimated applying an abrasive model. In contrast, in the tool area where the temperature is higher than the diffusive activation temperature, the wear rate can be evaluated applying a diffusive model. Finally, for a temperature ranges within the above cited values an adopted abrasive-diffusive wear model furnished the possibility to correctly evaluate the tool wear phenomena.

  13. A Comparative Study of Teacher Education Institutions and Machine Tool Manufacturers to Determine Course Content for a Machine Tool Maintenance Course in the Woodworking Area.

    ERIC Educational Resources Information Center

    Polette, Douglas Lee

    To determine what type of maintenance training the prospective industrial arts teacher should receive in the woodworking area and how this information should be taught, a research instrument was constructed using information obtained from a review of relevant literature. Specific data on machine tool maintenance was gathered by the use of two…

  14. Controlling the type and the form of chip when machining steel

    NASA Astrophysics Data System (ADS)

    Gruby, S. V.; Lasukov, A. A.; Nekrasov, R. Yu; Politsinsky, E. V.; Arkhipova, D. A.

    2016-08-01

    The type of the chip produced in the process of machining influences many factors of production process. Controlling the type of chip when cutting metals is important for producing swarf chips and for easing its utilization as well as for protecting the machined surface, cutting tool and the worker. In the given work we provide the experimental data on machining structural steel with implanted tool. The authors show that it is possible to control the chip formation process to produce the required type of chip by selecting the material for machining the tool surface.

  15. Defining and Testing the Influence of Servo System Response on Machine Tool Compliance

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hopkins, D J

    2004-03-24

    Compliance can be defined as the measurement of displacement per unit of force applied e.g. nano-meters per Newton (m/N). Compliance is the reciprocal of stiffness. High stiffness means low compliance and visa versa. It is an important factor in machine tool characteristics because it reflects the ability of the machine axis to maintain a desired position as it encounters a force or torque. Static compliance is a measurement made with a constant force applied e.g. the average depth of cut. Dynamic compliance is a measurement made as a function of frequency, e.g. a fast too servo (FTS) that applies amore » varying cutting force or load, interrupted cuts and external disturbances such as ground vibrations or air conditioning induced forces on the machine. Compliance can be defined for both a linear and rotary axis of a machine tool. However, to properly define compliance for a rotary axis, the axis must allow a commanded angular position. Note that this excludes velocity only axes. In this paper, several factors are discussed that affect compliance but emphasis is placed on how the machine servo system plays a key role in compliance at low to mid frequency regions. The paper discusses several techniques for measuring compliance and provides examples of results from these measurements.« less

  16. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

    PubMed Central

    Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

    2015-01-01

    Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

  17. Application of carbide cutting tools with nano-structured multilayer composite coatings for turning austenitic steels, type 16Cr-10NI

    NASA Astrophysics Data System (ADS)

    Vereschaka, Alexey; Migranov, Mars; Oganyan, Gaik; Sotova, Catherine S.; Batako, Andre

    2018-03-01

    This paper addresses the challenges of increasing the efficiency of the machining of austenitic stainless steels AISI 321 and S31600 by application of cutting tools with multilayer composite nano-structured coatings. The main mechanical properties and internal structures of the coatings under study (hardness, adhesion strength in the "coating-substrate" system) were investigated, and their chemical compositions were analyzed. The conducted research of tool life and nature of wear of carbide tools with the investigated coatings during turning of the above mentioned steels showed that the application of those coatings increases the tool life by up to 2.5 times. In addition, the use of a cutting tool with coatings allows machining at higher cutting speeds. It was also found that the use of a tool with multilayer composite nano-structured coating (Zr,Nb)N-(Zr,Al,Nb)N ensures better results compared with not only monolithic coating TiN, but also with nano-structured coatings Ti-TiN-(Ti,Al)N and (Zr,Nb)N-(Cr,Zr,Nb,Al)N. The mechanism of failure of the coatings under study was also investigated.

  18. Modeling and simulation of the fluid flow in wire electrochemical machining with rotating tool (wire ECM)

    NASA Astrophysics Data System (ADS)

    Klocke, F.; Herrig, T.; Zeis, M.; Klink, A.

    2017-10-01

    Combining the working principle of electrochemical machining (ECM) with a universal rotating tool, like a wire, could manage lots of challenges of the classical ECM sinking process. Such a wire-ECM process could be able to machine flexible and efficient 2.5-dimensional geometries like fir tree slots in turbine discs. Nowadays, established manufacturing technologies for slotting turbine discs are broaching and wire electrical discharge machining (wire EDM). Nevertheless, high requirements on surface integrity of turbine parts need cost intensive process development and - in case of wire-EDM - trim cuts to reduce the heat affected rim zone. Due to the process specific advantages, ECM is an attractive alternative manufacturing technology and is getting more and more relevant for sinking applications within the last few years. But ECM is also opposed with high costs for process development and complex electrolyte flow devices. In the past, few studies dealt with the development of a wire ECM process to meet these challenges. However, previous concepts of wire ECM were only suitable for micro machining applications. Due to insufficient flushing concepts the application of the process for machining macro geometries failed. Therefore, this paper presents the modeling and simulation of a new flushing approach for process assessment. The suitability of a rotating structured wire electrode in combination with an axial flushing for electrodes with high aspect ratios is investigated and discussed.

  19. Machine Tool Advanced Skills Technology Program (MAST). Overview and Methodology.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    The Machine Tool Advanced Skills Technology Program (MAST) is a geographical partnership of six of the nation's best two-year colleges located in the six states that have about one-third of the density of metals-related industries in the United States. The purpose of the MAST grant is to develop and implement a national training model to overcome…

  20. Machine Tool Technology. Automatic Screw Machine Troubleshooting & Set-Up Training Outlines [and] Basic Operator's Skills Set List.

    ERIC Educational Resources Information Center

    Anoka-Hennepin Technical Coll., Minneapolis, MN.

    This set of two training outlines and one basic skills set list are designed for a machine tool technology program developed during a project to retrain defense industry workers at risk of job loss or dislocation because of conversion of the defense industry. The first troubleshooting training outline lists the categories of problems that develop…

  1. Analysis and classification of the tools for assessing the risks associated with industrial machines.

    PubMed

    Paques, Joseph-Jean; Gauthier, François; Perez, Alejandro

    2007-01-01

    To assess and plan future risk-analysis research projects, 275 documents describing methods and tools for assessing the risks associated with industrial machines or with other sectors such as the military, and the nuclear and aeronautics industries, etc., were collected. These documents were in the format of published books or papers, standards, technical guides and company procedures collected throughout industry. From the collected documents, 112 documents were selected for analysis; 108 methods applied or potentially applicable for assessing the risks associated with industrial machines were analyzed and classified. This paper presents the main quantitative results of the analysis of the methods and tools.

  2. Study on effect of tool electrodes on surface finish during electrical discharge machining of Nitinol

    NASA Astrophysics Data System (ADS)

    Sahu, Anshuman Kumar; Chatterjee, Suman; Nayak, Praveen Kumar; Sankar Mahapatra, Siba

    2018-03-01

    Electrical discharge machining (EDM) is a non-traditional machining process which is widely used in machining of difficult-to-machine materials. EDM process can produce complex and intrinsic shaped component made of difficult-to-machine materials, largely applied in aerospace, biomedical, die and mold making industries. To meet the required applications, the EDMed components need to possess high accuracy and excellent surface finish. In this work, EDM process is performed using Nitinol as work piece material and AlSiMg prepared by selective laser sintering (SLS) as tool electrode along with conventional copper and graphite electrodes. The SLS is a rapid prototyping (RP) method to produce complex metallic parts by additive manufacturing (AM) process. Experiments have been carried out varying different process parameters like open circuit voltage (V), discharge current (Ip), duty cycle (τ), pulse-on-time (Ton) and tool material. The surface roughness parameter like average roughness (Ra), maximum height of the profile (Rt) and average height of the profile (Rz) are measured using surface roughness measuring instrument (Talysurf). To reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L27 orthogonal array has been chosen. The surface properties of the EDM specimen are optimized by desirability function approach and the best parametric setting is reported for the EDM process. Type of tool happens to be the most significant parameter followed by interaction of tool type and duty cycle, duty cycle, discharge current and voltage. Better surface finish of EDMed specimen can be obtained with low value of voltage (V), discharge current (Ip), duty cycle (τ) and pulse on time (Ton) along with the use of AlSiMg RP electrode.

  3. A new optimization tool path planning for 3-axis end milling of free-form surfaces based on efficient machining intervals

    NASA Astrophysics Data System (ADS)

    Vu, Duy-Duc; Monies, Frédéric; Rubio, Walter

    2018-05-01

    A large number of studies, based on 3-axis end milling of free-form surfaces, seek to optimize tool path planning. Approaches try to optimize the machining time by reducing the total tool path length while respecting the criterion of the maximum scallop height. Theoretically, the tool path trajectories that remove the most material follow the directions in which the machined width is the largest. The free-form surface is often considered as a single machining area. Therefore, the optimization on the entire surface is limited. Indeed, it is difficult to define tool trajectories with optimal feed directions which generate largest machined widths. Another limiting point of previous approaches for effectively reduce machining time is the inadequate choice of the tool. Researchers use generally a spherical tool on the entire surface. However, the gains proposed by these different methods developed with these tools lead to relatively small time savings. Therefore, this study proposes a new method, using toroidal milling tools, for generating toolpaths in different regions on the machining surface. The surface is divided into several regions based on machining intervals. These intervals ensure that the effective radius of the tool, at each cutter-contact points on the surface, is always greater than the radius of the tool in an optimized feed direction. A parallel plane strategy is then used on the sub-surfaces with an optimal specific feed direction for each sub-surface. This method allows one to mill the entire surface with efficiency greater than with the use of a spherical tool. The proposed method is calculated and modeled using Maple software to find optimal regions and feed directions in each region. This new method is tested on a free-form surface. A comparison is made with a spherical cutter to show the significant gains obtained with a toroidal milling cutter. Comparisons with CAM software and experimental validations are also done. The results show the

  4. Editing of EIA coded, numerically controlled, machine tool tapes

    NASA Technical Reports Server (NTRS)

    Weiner, J. M.

    1975-01-01

    Editing of numerically controlled (N/C) machine tool tapes (8-level paper tape) using an interactive graphic display processor is described. A rapid technique required for correcting production errors in N/C tapes was developed using the interactive text editor on the IMLAC PDS-ID graphic display system and two special programs resident on disk. The correction technique and special programs for processing N/C tapes coded to EIA specifications are discussed.

  5. A Catalog of Performance Objectives, Performance Conditions, and Performance Guides for Machine Tool Operations.

    ERIC Educational Resources Information Center

    Stadt, Ronald; And Others

    This catalog provides performance objectives, tasks, standards, and performance guides associated with current occupational information relating to the job content of machinists, specifically tool grinder operators, production lathe operators, and production screw machine operators. The catalog is comprised of 262 performance objectives, tool and…

  6. A Tool for Assessing the Text Legibility of Digital Human Machine Interfaces

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Roger Lew; Ronald L. Boring; Thomas A. Ulrich

    2015-08-01

    A tool intended to aid qualified professionals in the assessment of the legibility of text presented on a digital display is described. The assessment of legibility is primarily for the purposes of designing and analyzing human machine interfaces in accordance with NUREG-0700 and MIL-STD 1472G. The tool addresses shortcomings of existing guidelines by providing more accurate metrics of text legibility with greater sensitivity to design alternatives.

  7. High accurate interpolation of NURBS tool path for CNC machine tools

    NASA Astrophysics Data System (ADS)

    Liu, Qiang; Liu, Huan; Yuan, Songmei

    2016-09-01

    Feedrate fluctuation caused by approximation errors of interpolation methods has great effects on machining quality in NURBS interpolation, but few methods can efficiently eliminate or reduce it to a satisfying level without sacrificing the computing efficiency at present. In order to solve this problem, a high accurate interpolation method for NURBS tool path is proposed. The proposed method can efficiently reduce the feedrate fluctuation by forming a quartic equation with respect to the curve parameter increment, which can be efficiently solved by analytic methods in real-time. Theoretically, the proposed method can totally eliminate the feedrate fluctuation for any 2nd degree NURBS curves and can interpolate 3rd degree NURBS curves with minimal feedrate fluctuation. Moreover, a smooth feedrate planning algorithm is also proposed to generate smooth tool motion with considering multiple constraints and scheduling errors by an efficient planning strategy. Experiments are conducted to verify the feasibility and applicability of the proposed method. This research presents a novel NURBS interpolation method with not only high accuracy but also satisfying computing efficiency.

  8. Energy landscapes for machine learning

    NASA Astrophysics Data System (ADS)

    Ballard, Andrew J.; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D.; Wales, David J.

    Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

  9. Successful fabrication of a convex platform PMMA cell-counting slide using a high-precision perpendicular dual-spindle CNC machine tool

    NASA Astrophysics Data System (ADS)

    Chen, Shun-Tong; Chang, Chih-Hsien

    2013-12-01

    This study presents a novel approach to the fabrication of a biomedical-mold for producing convex platform PMMA (poly-methyl-meth-acrylate) slides for counting cells. These slides allow for the microscopic examination of urine sediment cells. Manufacturing of such slides incorporates three important procedures: (1) the development of a tabletop high-precision dual-spindle CNC (computerized numerical control) machine tool; (2) the formation of a boron-doped polycrystalline composite diamond (BD-PCD) wheel-tool on the machine tool developed in procedure (1); and (3) the cutting of a multi-groove-biomedical-mold array using the formed diamond wheel-tool in situ on the developed machine. The machine incorporates a hybrid working platform providing wheel-tool thinning using spark erosion to cut, polish, and deburr microgrooves on NAK80 steel directly. With consideration given for the electrical conductive properties of BD-PCD, the diamond wheel-tool is thinned to a thickness of 5 µm by rotary wire electrical discharge machining. The thinned wheel-tool can grind microgrooves 10 µm wide. An embedded design, which inserts a close fitting precision core into the biomedical-mold to create step-difference (concave inward) of 50 µm in height between the core and the mold, is also proposed and realized. The perpendicular dual-spindles and precision rotary stage are features that allow for biomedical-mold machining without the necessity of uploading and repositioning materials until all tasks are completed. A PMMA biomedical-slide with a plurality of juxtaposed counting chambers is formed and its usefulness verified.

  10. Machined Titanium Heat-Pipe Wick Structure

    NASA Technical Reports Server (NTRS)

    Rosenfeld, John H.; Minnerly, Kenneth G.; Gernert, Nelson J.

    2009-01-01

    Wick structures fabricated by machining of titanium porous material are essential components of lightweight titanium/ water heat pipes of a type now being developed for operation at temperatures up to 530 K in high-radiation environments. In the fabrication of some prior heat pipes, wicks have been made by extruding axial grooves into aluminum unfortunately, titanium cannot be extruded. In the fabrication of some other prior heat pipes, wicks have been made by in-situ sintering of metal powders shaped by the use of forming mandrels that are subsequently removed, but in the specific application that gave rise to the present fabrication method, the required dimensions and shapes of the heat-pipe structures would make it very difficult if not impossible to remove the mandrels due to the length and the small diameter. In the present method, a wick is made from one or more sections that are fabricated separately and assembled outside the tube that constitutes the outer heat pipe wall. The starting wick material is a slab of porous titanium material. This material is machined in its original flat configuration to form axial grooves. In addition, interlocking features are machined at the mating ends of short wick sections that are to be assembled to make a full-length continuous wick structure. Once the sections have been thus assembled, the resulting full-length flat wick structure is rolled into a cylindrical shape and inserted in the heatpipe tube (see figure). This wick-structure fabrication method is not limited to titanium/water heat pipes: It could be extended to other heat pipe materials and working fluids in which the wicks could be made from materials that could be pre-formed into porous slabs.

  11. MACHINE TOOL OPERATOR--GENERAL, ENTRY, SUGGESTED GUIDE FOR A TRAINING COURSE.

    ERIC Educational Resources Information Center

    RONEY, MAURICE W.; AND OTHERS

    THE PURPOSE OF THIS CURRICULUM GUIDE IS TO ASSIST THE ADMINISTRATOR AND INSTRUCTOR IN PLANNING AND DEVELOPING MANPOWER DEVELOPMENT AND TRAINING PROGRAMS TO PREPARE MACHINE TOOL OPERATORS FOR ENTRY-LEVEL POSITIONS. THE COURSE OUTLINE PROVIDES UNITS IN -- (1) ORIENTATION, (2) BENCH WORK, (3) SHOP MATHEMATICS, (4) BLUEPRINT READING AND SKETCHING, (5)…

  12. Analyzing the effect of cutting parameters on surface roughness and tool wear when machining nickel based hastelloy - 276

    NASA Astrophysics Data System (ADS)

    Khidhir, Basim A.; Mohamed, Bashir

    2011-02-01

    Machining parameters has an important factor on tool wear and surface finish, for that the manufacturers need to obtain optimal operating parameters with a minimum set of experiments as well as minimizing the simulations in order to reduce machining set up costs. The cutting speed is one of the most important cutting parameter to evaluate, it clearly most influences on one hand, tool life, tool stability, and cutting process quality, and on the other hand controls production flow. Due to more demanding manufacturing systems, the requirements for reliable technological information have increased. For a reliable analysis in cutting, the cutting zone (tip insert-workpiece-chip system) as the mechanics of cutting in this area are very complicated, the chip is formed in the shear plane (entrance the shear zone) and is shape in the sliding plane. The temperature contributed in the primary shear, chamfer and sticking, sliding zones are expressed as a function of unknown shear angle on the rake face and temperature modified flow stress in each zone. The experiments were carried out on a CNC lathe and surface finish and tool tip wear are measured in process. Machining experiments are conducted. Reasonable agreement is observed under turning with high depth of cut. Results of this research help to guide the design of new cutting tool materials and the studies on evaluation of machining parameters to further advance the productivity of nickel based alloy Hastelloy - 276 machining.

  13. Ion beam figuring of highly steep mirrors with a 5-axis hybrid machine tool

    NASA Astrophysics Data System (ADS)

    Yin, Xiaolin; Tang, Wa; Hu, Haixiang; Zeng, Xuefeng; Wang, Dekang; Xue, Donglin; Zhang, Feng; Deng, Weijie; Zhang, Xuejun

    2018-02-01

    Ion beam figuring (IBF) is an advanced and deterministic method for optical mirror surface processing. The removal function of IBF varies with the different incident angles of ion beam. Therefore, for the curved surface especially the highly steep one, the Ion Beam Source (IBS) should be equipped with 5-axis machining capability to remove the material along the normal direction of the mirror surface, so as to ensure the stability of the removal function. Based on the 3-RPS parallel mechanism and two dimensional displacement platform, a new type of 5-axis hybrid machine tool for IBF is presented. With the hybrid machine tool, the figuring process of a highly steep fused silica spherical mirror is introduced. The R/# of the mirror is 0.96 and the aperture is 104mm. The figuring result shows that, PV value of the mirror surface error is converged from 121.1nm to32.3nm, and RMS value 23.6nm to 3.4nm.

  14. Effect of High-speed Milling tool path strategies on the surface roughness of Stavax ESR mold insert machining

    NASA Astrophysics Data System (ADS)

    Mebrahitom, A.; Rizuan, D.; Azmir, M.; Nassif, M.

    2016-02-01

    High speed milling is one of the recent technologies used to produce mould inserts due to the need for high surface finish. It is a faster machining process where it uses a small side step and a small down step combined with very high spindle speed and feed rate. In order to effectively use the HSM capabilities, optimizing the tool path strategies and machining parameters is an important issue. In this paper, six different tool path strategies have been investigated on the surface finish and machining time of a rectangular cavities of ESR Stavax material. CAD/CAM application of CATIA V5 machining module for pocket milling of the cavities was used for process planning.

  15. Web-Based Machine Translation as a Tool for Promoting Electronic Literacy and Language Awareness

    ERIC Educational Resources Information Center

    Williams, Lawrence

    2006-01-01

    This article addresses a pervasive problem of concern to teachers of many foreign languages: the use of Web-Based Machine Translation (WBMT) by students who do not understand the complexities of this relatively new tool. Although networked technologies have greatly increased access to many language and communication tools, WBMT is still…

  16. 76 FR 5832 - International Business Machines (IBM), Software Group Business Unit, Optim Data Studio Tools QA...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-02

    ... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-74,554] International Business Machines (IBM), Software Group Business Unit, Optim Data Studio Tools QA, San Jose, CA; Notice of... determination of the TAA petition filed on behalf of workers at International Business Machines (IBM), Software...

  17. Performance of Ti-multilayer coated tool during machining of MDN431 alloyed steel

    NASA Astrophysics Data System (ADS)

    Badiger, Pradeep V.; Desai, Vijay; Ramesh, M. R.

    2018-04-01

    Turbine forgings and other components are required to be high resistance to corrosion and oxidation because which they are highly alloyed with Ni and Cr. Midhani manufactures one of such material MDN431. It's a hard-to-machine steel with high hardness and strength. PVD coated insert provide an answer to problem with its state of art technique on the WC tool. Machinability studies is carried out on MDN431 steel using uncoated and Ti-multilayer coated WC tool insert using Taguchi optimisation technique. During the present investigation, speed (398-625rpm), feed (0.093-0.175mm/rev), and depth of cut (0.2-0.4mm) varied according to Taguchi L9 orthogonal array, subsequently cutting forces and surface roughness (Ra) were measured. Optimizations of the obtained results are done using Taguchi technique for cutting forces and surface roughness. Using Taguchi technique linear fit model regression analysis carried out for the combination of each input variable. Experimented results are compared and found the developed model is adequate which supported by proof trials. Speed, feed and depth of cut are linearly dependent on the cutting force and surface roughness for uncoated insert whereas Speed and depth of cut feed is inversely dependent in coated insert for both cutting force and surface roughness. Machined surface for coated and uncoated inserts during machining of MDN431 is studied using optical profilometer.

  18. Impact of heat treatment on HSS cutting tool (ASTM A600) and its behaviour during machining of mild steel (ASTM A36)

    NASA Astrophysics Data System (ADS)

    Afolalu, S. A.; Abioye, O. P.; Salawu, E. Y.; Okokpujie, I. P.; Abioye, A. A.; Omotosho, O. A.; Ajayi., O. O.

    2018-04-01

    Carburization is one the best heat treatment that responded well to hardening with Palm Kernel Shell giving the best hardness value. This work studied the influence of carburization on HSStool(ASTM A600) and its behaviour during machining of mild steel (ASTM A36). Composition of the samples (12 pieces of 180 × 12 × 12 mm) HSS tools were checked using UV-VIS spectrometer and the tools were carburized with PKS at holding temperatures and time of 800, 850, 900, 950 °C and 60,90 120 minutes using muffle furnance. The micro structural analysis, surface and core hardnessof the treated samples gave better results than the untreated samples when checked withsoft driven and optical microscope. It wasalso observed that increase in the feed rate and depth for length of cut of 50 mm significantly reduces the wear progression and thereby gave best machining time at maximum carburizing temperature and time(950 °C / 120 minutes) when it was used to cut mild steelon the lathe machine.

  19. In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts

    PubMed Central

    Yang, Hongbin; Sun, Lixia; Li, Weihua; Liu, Guixia; Tang, Yun

    2018-01-01

    During drug development, safety is always the most important issue, including a variety of toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial phases. This review article at first simply introduced the computational methods used in prediction of chemical toxicity for drug design, including machine learning methods and structural alerts. Machine learning methods have been widely applied in qualitative classification and quantitative regression studies, while structural alerts can be regarded as a complementary tool for lead optimization. The emphasis of this article was put on the recent progress of predictive models built for various toxicities. Available databases and web servers were also provided. Though the methods and models are very helpful for drug design, there are still some challenges and limitations to be improved for drug safety assessment in the future. PMID:29515993

  20. In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts

    NASA Astrophysics Data System (ADS)

    Yang, Hongbin; Sun, Lixia; Li, Weihua; Liu, Guixia; Tang, Yun

    2018-02-01

    For a drug, safety is always the most important issue, including a variety of toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial phases. This review article at first simply introduced the computational methods used in prediction of chemical toxicity for drug design, including machine learning methods and structural alerts. Machine learning methods have been widely applied in qualitative classification and quantitative regression studies, while structural alerts can be regarded as a complementary tool for lead optimization. The emphasis of this article was put on the recent progress of predictive models built for various toxicities. Available databases and web servers were also provided. Though the methods and models are very helpful for drug design, there are still some challenges and limitations to be improved for drug safety assessment in the future.

  1. Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

    PubMed

    Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

    2009-05-01

    Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

  2. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 1: Executive Summary, of a 15-Volume Set of Skills Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    The Machine Tool Advanced Skills Technology (MAST) consortium was formed to address the shortage of skilled workers for the machine tools and metals-related industries. Featuring six of the nation's leading advanced technology centers, the MAST consortium developed, tested, and disseminated industry-specific skill standards and model curricula for…

  3. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 15: Administrative Information, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This volume developed by the Machine Tool Advanced Skill Technology (MAST) program contains key administrative documents and provides additional sources for machine tool and precision manufacturing information and important points of contact in the industry. The document contains the following sections: a foreword; grant award letter; timeline for…

  4. Study of Tool Wear Mechanisms and Mathematical Modeling of Flank Wear During Machining of Ti Alloy (Ti6Al4V)

    NASA Astrophysics Data System (ADS)

    Chetan; Narasimhulu, A.; Ghosh, S.; Rao, P. V.

    2015-07-01

    Machinability of titanium is poor due to its low thermal conductivity and high chemical affinity. Lower thermal conductivity of titanium alloy is undesirable on the part of cutting tool causing extensive tool wear. The main task of this work is to predict the various wear mechanisms involved during machining of Ti alloy (Ti6Al4V) and to formulate an analytical mathematical tool wear model for the same. It has been found from various experiments that adhesive and diffusion wear are the dominating wear during machining of Ti alloy with PVD coated tungsten carbide tool. It is also clear from the experiments that the tool wear increases with the increase in cutting parameters like speed, feed and depth of cut. The wear model was validated by carrying out dry machining of Ti alloy at suitable cutting conditions. It has been found that the wear model is able to predict the flank wear suitably under gentle cutting conditions.

  5. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 6: Welding, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  6. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 12: Instrumentation, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  7. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 5: Mold Making, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational speciality areas within the U.S. machine tool and metals-related…

  8. Modeling of Passive Forces of Machine Tool Covers

    NASA Astrophysics Data System (ADS)

    Kolar, Petr; Hudec, Jan; Sulitka, Matej

    The passive forces acting against the drive force are phenomena that influence dynamical properties and precision of linear axes equipped with feed drives. Covers are one of important sources of passive forces in machine tools. The paper describes virtual evaluation of cover passive forces using the cover complex model. The model is able to compute interaction between flexible cover segments and sealing wiper. The result is deformation of cover segments and wipers which is used together with measured friction coefficient for computation of cover total passive force. This resulting passive force is dependent on cover position. Comparison of computational results and measurement on the real cover is presented in the paper.

  9. Acoustic emission from single point machining: Part 2, Signal changes with tool wear

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Heiple, C.R.; Carpenter, S.H.; Armentrout, D.L.

    1989-01-01

    Changes in acoustic emission signal characteristics with tool wear were monitored during single point machining of 4340 steel and Ti-6Al-4V heat treated to several strength levels, 606l-T6 aluminum, 304 stainless steel, 17-4PH stainless steel, 410 stainless steel, lead, and teflon. No signal characteristic changed in the same way with tool wear for all materials tested. A single change in a particular AE signal characteristic with tool wear valid for all materials probably does not exist. Nevertheless, changes in various signal characteristic with wear for a given material may be sufficient to be used to monitor tool wear.

  10. Swept Mechanism of Micro-Milling Tool Geometry Effect on Machined Oxygen Free High Conductivity Copper (OFHC) Surface Roughness

    PubMed Central

    Shi, Zhenyu; Liu, Zhanqiang; Li, Yuchao; Qiao, Yang

    2017-01-01

    Cutting tool geometry should be very much considered in micro-cutting because it has a significant effect on the topography and accuracy of the machined surface, particularly considering the uncut chip thickness is comparable to the cutting edge radius. The objective of this paper was to clarify the influence of the mechanism of the cutting tool geometry on the surface topography in the micro-milling process. Four different cutting tools including two two-fluted end milling tools with different helix angles of 15° and 30° cutting tools, as well as two three-fluted end milling tools with different helix angles of 15° and 30° were investigated by combining theoretical modeling analysis with experimental research. The tool geometry was mathematically modeled through coordinate translation and transformation to make all three cutting edges at the cutting tool tip into the same coordinate system. Swept mechanisms, minimum uncut chip thickness, and cutting tool run-out were considered on modeling surface roughness parameters (the height of surface roughness Rz and average surface roughness Ra) based on the established mathematical model. A set of cutting experiments was carried out using four different shaped cutting tools. It was found that the sweeping volume of the cutting tool increases with the decrease of both the cutting tool helix angle and the flute number. Great coarse machined surface roughness and more non-uniform surface topography are generated when the sweeping volume increases. The outcome of this research should bring about new methodologies for micro-end milling tool design and manufacturing. The machined surface roughness can be improved by appropriately selecting the tool geometrical parameters. PMID:28772479

  11. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 8: Sheet Metal & Composites, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  12. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 4: Manufacturing Engineering Technology, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  13. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 14: Automated Equipment Technician (CIM), of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  14. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 10: Computer-Aided Drafting & Design, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  15. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 7: Industrial Maintenance Technology, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  16. Tool grinding machine

    DOEpatents

    Dial, Sr., Charles E.

    1980-01-01

    The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thickness may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

  17. Augmentation of machine structure to improve its diagnosability

    NASA Technical Reports Server (NTRS)

    Hsieh, L.

    1973-01-01

    Two methods of augmenting the structure of a sequential machine so that it is diagnosable are presented. The checkable (checking sequences) and repeated symbol distinguishing sequences (RDS) are discussed. It was found that as few as twice the number of outputs of the given machine is sufficient for constructing a state-output augmentation with RDS. Techniques for minimizing the number of states in resolving convergences and in resolving equivalent and nonreduced cycles are developed.

  18. Error compensation for thermally induced errors on a machine tool

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Krulewich, D.A.

    1996-11-08

    Heat flow from internal and external sources and the environment create machine deformations, resulting in positioning errors between the tool and workpiece. There is no industrially accepted method for thermal error compensation. A simple model has been selected that linearly relates discrete temperature measurements to the deflection. The biggest problem is how to locate the temperature sensors and to determine the number of required temperature sensors. This research develops a method to determine the number and location of temperature measurements.

  19. Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

    NASA Astrophysics Data System (ADS)

    Mahapatra, Prasant Kumar; Sethi, Spardha; Kumar, Amod

    2015-10-01

    In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

  20. Mounting arrangement for the drive system of an air-bearing spindle on a machine tool

    DOEpatents

    Lunsford, J.S.; Crisp, D.W.; Petrowski, P.L.

    1987-12-07

    The present invention is directed to a mounting arrangement for the drive system of an air-bearing spindle utilized on a machine tool such as a lathe. The mounting arrangement of the present invention comprises a housing which is secured to the casing of the air bearing in such a manner that the housing position can be selectively adjusted to provide alignment of the air-bearing drive shaft supported by the housing and the air-bearing spindle. Once this alignment is achieved the air between spindle and the drive arrangement is maintained in permanent alignment so as to overcome misalignment problems encountered in the operation of the machine tool between the air-bearing spindle and the shaft utilized for driving the air-bearing spindle.

  1. The Impact Of Surface Shape Of Chip-Breaker On Machined Surface

    NASA Astrophysics Data System (ADS)

    Šajgalík, Michal; Czán, Andrej; Martinček, Juraj; Varga, Daniel; Hemžský, Pavel; Pitela, David

    2015-12-01

    Machined surface is one of the most used indicators of workpiece quality. But machined surface is influenced by several factors such as cutting parameters, cutting material, shape of cutting tool or cutting insert, micro-structure of machined material and other known as technological parameters. By improving of these parameters, we can improve machined surface. In the machining, there is important to identify the characteristics of main product of these processes - workpiece, but also the byproduct - the chip. Size and shape of chip has impact on lifetime of cutting tools and its inappropriate form can influence the machine functionality and lifetime, too. This article deals with elimination of long chip created when machining of shaft in automotive industry and with impact of shape of chip-breaker on shape of chip in various cutting conditions based on production requirements.

  2. Reducing maintenance costs in agreement with CNC machine tools reliability

    NASA Astrophysics Data System (ADS)

    Ungureanu, A. L.; Stan, G.; Butunoi, P. A.

    2016-08-01

    Aligning maintenance strategy with reliability is a challenge due to the need to find an optimal balance between them. Because the various methods described in the relevant literature involve laborious calculations or use of software that can be costly, this paper proposes a method that is easier to implement on CNC machine tools. The new method, called the Consequence of Failure Analysis (CFA) is based on technical and economic optimization, aimed at obtaining a level of required performance with minimum investment and maintenance costs.

  3. Market for multiaxis laser machine tools

    NASA Astrophysics Data System (ADS)

    Ream, Stanley L.

    1991-03-01

    While it's true that this is an exciting topic, it niay be more exciting than profitable, but it certainly has captured the attention of a lot of us laser folks, and it keeps growing almost because it wants to. First of all let me comment briefly with a word from our sponsor that GE Fanuc is one of the several ways the Fanuc laser product gets into the United States. We market it, GM Fanuc also markets it, and of course it shows up on Japanese machine tool built products. The information in this little presentation came from discussions with you folks wherever possible. In some cases I was unable to make contact with the horse's mouth as it were, but we got roundabout information so it's not gospel, but it's close. We've also had some updated information at the show here updated rumors maybe that suggest that some of the numbers may be high or low. I think in the aggregate it's not too far off.

  4. Thrown object testing of forest machine operator protective structures

    Treesearch

    S.E. Taylor; M.W. Veal; R.B. Rummer

    2003-01-01

    High-speed chains or rotating disks are commonly used to cut and process trees during forest harvesting operations. Mechanical failure or fatigue of these tools can lead to a potentially hazardous situation where fragments of chain or sawteeth are thrown through the operator enclosures on forest machines. This poster presentation discusses the development and...

  5. Influence of Cutting Parameters and Tool Wear on the Surface Integrity of Cobalt-Based Stellite 6 Alloy When Machined Under a Dry Cutting Environment

    NASA Astrophysics Data System (ADS)

    Yingfei, Ge; de Escalona, Patricia Muñoz; Galloway, Alexander

    2017-01-01

    The efficiency of a machining process can be measured by evaluating the quality of the machined surface and the tool wear rate. The research reported herein is mainly focused on the effect of cutting parameters and tool wear on the machined surface defects, surface roughness, deformation layer and residual stresses when dry milling Stellite 6, deposited by overlay on a carbon steel surface. The results showed that under the selected cutting conditions, abrasion, diffusion, peeling, chipping and breakage were the main tool wear mechanisms presented. Also the feed rate was the primary factor affecting the tool wear with an influence of 83%. With regard to the influence of cutting parameters on the surface roughness, the primary factors were feed rate and cutting speed with 57 and 38%, respectively. In addition, in general, as tool wear increased, the surface roughness increased and the deformation layer was found to be influenced more by the cutting parameters rather than the tool wear. Compressive residual stresses were observed in the un-machined surface, and when machining longer than 5 min, residual stress changed 100% from compression to tension. Finally, results showed that micro-crack initiation was the main mechanism for chip formation.

  6. Machine learning for autonomous crystal structure identification.

    PubMed

    Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

    2017-07-21

    We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

  7. Research of a smart cutting tool based on MEMS strain gauge

    NASA Astrophysics Data System (ADS)

    Zhao, Y.; Zhao, Y. L.; Shao, YW; Hu, T. J.; Zhang, Q.; Ge, X. H.

    2018-03-01

    Cutting force is an important factor that affects machining accuracy, cutting vibration and tool wear. Machining condition monitoring by cutting force measurement is a key technology for intelligent manufacture. Current cutting force sensors exist problems of large volume, complex structure and poor compatibility in practical application, for these problems, a smart cutting tool is proposed in this paper for cutting force measurement. Commercial MEMS (Micro-Electro-Mechanical System) strain gauges with high sensitivity and small size are adopted as transducing element of the smart tool, and a structure optimized cutting tool is fabricated for MEMS strain gauge bonding. Static calibration results show that the developed smart cutting tool is able to measure cutting forces in both X and Y directions, and the cross-interference error is within 3%. Its general accuracy is 3.35% and 3.27% in X and Y directions, and sensitivity is 0.1 mV/N, which is very suitable for measuring small cutting forces in high speed and precision machining. The smart cutting tool is portable and reliable for practical application in CNC machine tool.

  8. Acoustic emission from single point machining: Part 2, Signal changes with tool wear. Revised

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Heiple, C.R.; Carpenter, S.H.; Armentrout, D.L.

    1989-12-31

    Changes in acoustic emission signal characteristics with tool wear were monitored during single point machining of 4340 steel and Ti-6Al-4V heat treated to several strength levels, 606l-T6 aluminum, 304 stainless steel, 17-4PH stainless steel, 410 stainless steel, lead, and teflon. No signal characteristic changed in the same way with tool wear for all materials tested. A single change in a particular AE signal characteristic with tool wear valid for all materials probably does not exist. Nevertheless, changes in various signal characteristic with wear for a given material may be sufficient to be used to monitor tool wear.

  9. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 11: Computer-Aided Manufacturing & Advanced CNC, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  10. Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 2: Career Development, General Education and Remediation, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

    ERIC Educational Resources Information Center

    Texas State Technical Coll., Waco.

    This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

  11. Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

    PubMed

    Podlewska, Sabina; Czarnecki, Wojciech M; Kafel, Rafał; Bojarski, Andrzej J

    2017-02-27

    The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at http://skandal.if-pan.krakow.pl/comb_lib/ .

  12. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition.

    PubMed

    Caggiano, Alessandra

    2018-03-09

    Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features ( k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear ( VB max ) was achieved, with predicted values very close to the measured tool wear values.

  13. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

    PubMed Central

    2018-01-01

    Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features (k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear (VBmax) was achieved, with predicted values very close to the measured tool wear values. PMID:29522443

  14. Dust Emission Induced By Friction Modifications At Tool Chip Interface In Dry Machining In MMCp

    NASA Astrophysics Data System (ADS)

    Kremer, Arnaud; El Mansori, Mohamed

    2011-01-01

    This paper investigates the relationship between dust emission and tribological conditions at the tool-chip interface when machining Metal Matrix composite reinforced with particles (MMCp) in dry mode. Machining generates aerosols that can easily be inhaled by workers. Aerosols may be composed of oil mist, tool material or alloying elements of workpiece material. Bar turning tests were conducted on a 2009 aluminum alloy reinforced with different level of Silicon Carbide particles (15, 25 and 35% of SiCp). Variety of PCD tools and nanostructured diamond coatings were used to analyze their performances on air pollution. A spectrometer was used to detect airborne aerosol particles in the size range between 0.3μm to 20 μm and to sort them in 15 size channels in real time. It was used to compare the effects of test parameters on dust emission. Observations of tool face and chip morphology reveal the importance of friction phenomena. It was demonstrated that level of friction modifies chip curvature and dust emission. The increase of level of reinforcement increase the chip segmentation and decrease the contact length and friction area. A "running in" phenomenon with important dust emission appeared with PCD tool due to the tool rake face flatness. In addition dust generation is more sensitive to edge integrity than power consumption.

  15. Technology and Jobs: Computer-Aided Design. Numerical-Control Machine-Tool Operators. Office Automation.

    ERIC Educational Resources Information Center

    Stanton, Michael; And Others

    1985-01-01

    Three reports on the effects of high technology on the nature of work include (1) Stanton on applications and implications of computer-aided design for engineers, drafters, and architects; (2) Nardone on the outlook and training of numerical-control machine tool operators; and (3) Austin and Drake on the future of clerical occupations in automated…

  16. The study on force, surface integrity, tool life and chip on laser assisted machining of inconel 718 using Nd:YAG laser source.

    PubMed

    Venkatesan, K

    2017-07-01

    Inconel 718, a high-temperature alloy, is a promising material for high-performance aerospace gas turbine engines components. However, the machining of the alloy is difficult owing to immense shear strength, rapid work hardening rate during turning, and less thermal conductivity. Hence, like ceramics and composites, the machining of this alloy is considered as difficult-to-turn materials. Laser assisted turning method has become a promising solution in recent years to lessen cutting stress when materials that are considered difficult-to-turn, such as Inconel 718 is employed. This study investigated the influence of input variables of laser assisted machining on the machinability aspect of the Inconel 718. The comparison of machining characteristics has been carried out to analyze the process benefits with the variation of laser machining variables. The laser assisted machining variables are cutting speeds of 60-150 m/min, feed rates of 0.05-0.125 mm/rev with a laser power between 1200 W and 1300 W. The various output characteristics such as force, roughness, tool life and geometrical characteristic of chip are investigated and compared with conventional machining without application of laser power. From experimental results, at a laser power of 1200 W, laser assisted turning outperforms conventional machining by 2.10 times lessening in cutting force, 46% reduction in surface roughness as well as 66% improvement in tool life when compared that of conventional machining. Compared to conventional machining, with the application of laser, the cutting speed of carbide tool has increased to a cutting condition of 150 m/min, 0.125 mm/rev. Microstructural analysis shows that no damage of the subsurface of the workpiece.

  17. From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

    PubMed

    Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

    2017-11-01

    Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Protein asparagine deamidation prediction based on structures with machine learning methods.

    PubMed

    Jia, Lei; Sun, Yaxiong

    2017-01-01

    Chemical stability is a major concern in the development of protein therapeutics due to its impact on both efficacy and safety. Protein "hotspots" are amino acid residues that are subject to various chemical modifications, including deamidation, isomerization, glycosylation, oxidation etc. A more accurate prediction method for potential hotspot residues would allow their elimination or reduction as early as possible in the drug discovery process. In this work, we focus on prediction models for asparagine (Asn) deamidation. Sequence-based prediction method simply identifies the NG motif (amino acid asparagine followed by a glycine) to be liable to deamidation. It still dominates deamidation evaluation process in most pharmaceutical setup due to its convenience. However, the simple sequence-based method is less accurate and often causes over-engineering a protein. We introduce structure-based prediction models by mining available experimental and structural data of deamidated proteins. Our training set contains 194 Asn residues from 25 proteins that all have available high-resolution crystal structures. Experimentally measured deamidation half-life of Asn in penta-peptides as well as 3D structure-based properties, such as solvent exposure, crystallographic B-factors, local secondary structure and dihedral angles etc., were used to train prediction models with several machine learning algorithms. The prediction tools were cross-validated as well as tested with an external test data set. The random forest model had high enrichment in ranking deamidated residues higher than non-deamidated residues while effectively eliminated false positive predictions. It is possible that such quantitative protein structure-function relationship tools can also be applied to other protein hotspot predictions. In addition, we extensively discussed metrics being used to evaluate the performance of predicting unbalanced data sets such as the deamidation case.

  19. Tube Alinement for Machining

    NASA Technical Reports Server (NTRS)

    Garcia, J.

    1984-01-01

    Tool with stepped shoulders alines tubes for machining in preparation for welding. Alinement with machine tool axis accurate to within 5 mils (0.13mm) and completed much faster than visual setup by machinist.

  20. Dynamic analysis and vibration testing of CFRP drive-line system used in heavy-duty machine tool

    NASA Astrophysics Data System (ADS)

    Yang, Mo; Gui, Lin; Hu, Yefa; Ding, Guoping; Song, Chunsheng

    2018-03-01

    Low critical rotary speed and large vibration in the metal drive-line system of heavy-duty machine tool affect the machining precision seriously. Replacing metal drive-line with the CFRP drive-line can effectively solve this problem. Based on the composite laminated theory and the transfer matrix method (TMM), this paper puts forward a modified TMM to analyze dynamic characteristics of CFRP drive-line system. With this modified TMM, the CFRP drive-line of a heavy vertical miller is analyzed. And the finite element modal analysis model of the shafting is established. The results of the modified TMM and finite element analysis (FEA) show that the modified TMM can effectively predict the critical rotary speed of CFRP drive-line. And the critical rotary speed of CFRP drive-line is 20% higher than that of the original metal drive-line. Then, the vibration of the CFRP and the metal drive-line were tested. The test results show that application of the CFRP drive shaft in the drive-line can effectively reduce the vibration of the heavy-duty machine tool.

  1. PredicT-ML: a tool for automating machine learning model building with big clinical data.

    PubMed

    Luo, Gang

    2016-01-01

    Predictive modeling is fundamental to transforming large clinical data sets, or "big clinical data," into actionable knowledge for various healthcare applications. Machine learning is a major predictive modeling approach, but two barriers make its use in healthcare challenging. First, a machine learning tool user must choose an algorithm and assign one or more model parameters called hyper-parameters before model training. The algorithm and hyper-parameter values used typically impact model accuracy by over 40 %, but their selection requires many labor-intensive manual iterations that can be difficult even for computer scientists. Second, many clinical attributes are repeatedly recorded over time, requiring temporal aggregation before predictive modeling can be performed. Many labor-intensive manual iterations are required to identify a good pair of aggregation period and operator for each clinical attribute. Both barriers result in time and human resource bottlenecks, and preclude healthcare administrators and researchers from asking a series of what-if questions when probing opportunities to use predictive models to improve outcomes and reduce costs. This paper describes our design of and vision for PredicT-ML (prediction tool using machine learning), a software system that aims to overcome these barriers and automate machine learning model building with big clinical data. The paper presents the detailed design of PredicT-ML. PredicT-ML will open the use of big clinical data to thousands of healthcare administrators and researchers and increase the ability to advance clinical research and improve healthcare.

  2. Servo scanning 3D micro EDM for array micro cavities using on-machine fabricated tool electrodes

    NASA Astrophysics Data System (ADS)

    Tong, Hao; Li, Yong; Zhang, Long

    2018-02-01

    Array micro cavities are useful in many fields including in micro molds, optical devices, biochips and so on. Array servo scanning micro electro discharge machining (EDM), using array micro electrodes with simple cross-sectional shape, has the advantage of machining complex 3D micro cavities in batches. In this paper, the machining errors caused by offline-fabricated array micro electrodes are analyzed in particular, and then a machining process of array servo scanning micro EDM is proposed by using on-machine fabricated array micro electrodes. The array micro electrodes are fabricated on-machine by combined procedures including wire electro discharge grinding, array reverse copying and electrode end trimming. Nine-array tool electrodes with Φ80 µm diameter and 600 µm length are obtained. Furthermore, the proposed process is verified by several machining experiments for achieving nine-array hexagonal micro cavities with top side length of 300 µm, bottom side length of 150 µm, and depth of 112 µm or 120 µm. In the experiments, a chip hump accumulates on the electrode tips like the built-up edge in mechanical machining under the conditions of brass workpieces, copper electrodes and the dielectric of deionized water. The accumulated hump can be avoided by replacing the water dielectric by an oil dielectric.

  3. Laser beam machining of polycrystalline diamond for cutting tool manufacturing

    NASA Astrophysics Data System (ADS)

    Wyszyński, Dominik; Ostrowski, Robert; Zwolak, Marek; Bryk, Witold

    2017-10-01

    The paper concerns application of DPSS Nd: YAG 532nm pulse laser source for machining of polycrystalline WC based diamond inserts (PCD). The goal of the research was to determine optimal laser cutting parameters for cutting tool shaping. Basic criteria to reach the goal was cutting edge quality (minimalization of finishing operations), material removal rate (time and cost efficiency), choice of laser beam characteristics (polarization, power, focused beam diameter). The research was planned and realised and analysed according to design of experiment rules (DOE). The analysis of the cutting edge was prepared with use of Alicona Infinite Focus measurement system.

  4. The research on construction and application of machining process knowledge base

    NASA Astrophysics Data System (ADS)

    Zhao, Tan; Qiao, Lihong; Qie, Yifan; Guo, Kai

    2018-03-01

    In order to realize the application of knowledge in machining process design, from the perspective of knowledge in the application of computer aided process planning(CAPP), a hierarchical structure of knowledge classification is established according to the characteristics of mechanical engineering field. The expression of machining process knowledge is structured by means of production rules and the object-oriented methods. Three kinds of knowledge base models are constructed according to the representation of machining process knowledge. In this paper, the definition and classification of machining process knowledge, knowledge model, and the application flow of the process design based on the knowledge base are given, and the main steps of the design decision of the machine tool are carried out as an application by using the knowledge base.

  5. Ultra precision machining

    NASA Astrophysics Data System (ADS)

    Debra, Daniel B.; Hesselink, Lambertus; Binford, Thomas

    1990-05-01

    There are a number of fields that require or can use to advantage very high precision in machining. For example, further development of high energy lasers and x ray astronomy depend critically on the manufacture of light weight reflecting metal optical components. To fabricate these optical components with machine tools they will be made of metal with mirror quality surface finish. By mirror quality surface finish, it is meant that the dimensions tolerances on the order of 0.02 microns and surface roughness of 0.07. These accuracy targets fall in the category of ultra precision machining. They cannot be achieved by a simple extension of conventional machining processes and techniques. They require single crystal diamond tools, special attention to vibration isolation, special isolation of machine metrology, and on line correction of imperfection in the motion of the machine carriages on their way.

  6. Vee-notch tool cuts specimens

    NASA Technical Reports Server (NTRS)

    Spier, R. A.

    1970-01-01

    Triangular cutting tool uses carbide tips for notching heat-treated or abrasive materials, and alloys subjected to high structural stresses. The tool is rigidly mounted in a slot of mating contour to prevent deflection during cutting of tensile specimens. No other expensive machine equipment is required.

  7. Structural and Machine Design Using Piezoceramic Materials: A Guide for Structural Design Engineers

    NASA Technical Reports Server (NTRS)

    Inman, Daniel J.; Cudney, Harley H.

    2000-01-01

    Using piezoceramic materials is one way the design engineer can create structures which have an ability to both sense and respond to their environment. Piezoceramic materials can be used to create structural sensors and structural actuators. Because piezoceramic materials have transduction as a material property, their sensing or actuation functions are a result of what happens to the material. This is different than discrete devices we might attach to the structure. For example, attaching an accelerometer to a structure will yield an electrical signal proportional to the acceleration at the attachment point on the structure. Using a electromagnetic shaker as an actuator will create an applied force at the attachment point. Active material elements in a structural design are not easily modeled as providing transduction at a point, but rather they change the physics of the structure in the areas where they are used. Hence, a designer must not think of adding discrete devices to a structure to obtain an effect, but rather must design a structural system which accounts for the physical principles of all the elements in the structure. The purpose of this manual is to provide practicing engineers the information necessary to incorporate piezoelectric materials in structural design and machine design. First, we will review the solid-state physics of piezoelectric materials. Then we will discuss the physical characteristics of the electrical-active material-structural system. We will present the elements of this system which must be considered as part of the design task for a structural engineer. We will cover simple modeling techniques and review the features and capabilities of commercial design tools that are available. We will then cover practical how-to elements of working with piezoceramic materials. We will review sources of piezoceramic materials and built-up devices, and their characteristics. Finally, we will provide two design examples using piezoceramic

  8. Tool setting device

    DOEpatents

    Brown, Raymond J.

    1977-01-01

    The present invention relates to a tool setting device for use with numerically controlled machine tools, such as lathes and milling machines. A reference position of the machine tool relative to the workpiece along both the X and Y axes is utilized by the control circuit for driving the tool through its program. This reference position is determined for both axes by displacing a single linear variable displacement transducer (LVDT) with the machine tool through a T-shaped pivotal bar. The use of the T-shaped bar allows the cutting tool to be moved sequentially in the X or Y direction for indicating the actual position of the machine tool relative to the predetermined desired position in the numerical control circuit by using a single LVDT.

  9. Investigation of machinability characteristics on EN47 steel for cutting force and tool wear using optimization technique

    NASA Astrophysics Data System (ADS)

    M, Vasu; Shivananda Nayaka, H.

    2018-06-01

    In this experimental work dry turning process carried out on EN47 spring steel with coated tungsten carbide tool insert with 0.8 mm nose radius are optimized by using statistical technique. Experiments were conducted at three different cutting speeds (625, 796 and 1250 rpm) with three different feed rates (0.046, 0.062 and 0.093 mm/rev) and depth of cuts (0.2, 0.3 and 0.4 mm). Experiments are conducted based on full factorial design (FFD) 33 three factors and three levels. Analysis of variance is used to identify significant factor for each output response. The result reveals that feed rate is the most significant factor influencing on cutting force followed by depth of cut and cutting speed having less significance. Optimum machining condition for cutting force obtained from the statistical technique. Tool wear measurements are performed with optimum condition of Vc = 796 rpm, ap = 0.2 mm, f = 0.046 mm/rev. The minimum tool wear observed as 0.086 mm with 5 min machining. Analysis of tool wear was done by confocal microscope it was observed that tool wear increases with increasing cutting time.

  10. Applications of Support Vector Machines In Chemo And Bioinformatics

    NASA Astrophysics Data System (ADS)

    Jayaraman, V. K.; Sundararajan, V.

    2010-10-01

    Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.

  11. A machine learning tool for re-planning and adaptive RT: A multicenter cohort investigation.

    PubMed

    Guidi, G; Maffei, N; Meduri, B; D'Angelo, E; Mistretta, G M; Ceroni, P; Ciarmatori, A; Bernabei, A; Maggi, S; Cardinali, M; Morabito, V E; Rosica, F; Malara, S; Savini, A; Orlandi, G; D'Ugo, C; Bunkheila, F; Bono, M; Lappi, S; Blasi, C; Lohr, F; Costi, T

    2016-12-01

    To predict patients who would benefit from adaptive radiotherapy (ART) and re-planning intervention based on machine learning from anatomical and dosimetric variations in a retrospective dataset. 90 patients (pts) treated for head-neck cancer (H&N) formed a multicenter data-set. 41 H&N pts (45.6%) were considered for learning; 49 pts (54.4%) were used to test the tool. A homemade machine-learning classifier was developed to analyze volume and dose variations of parotid glands (PG). Using deformable image registration (DIR) and GPU, patients' conditions were analyzed automatically. Support Vector Machines (SVM) was used for time-series evaluation. "Inadequate" class identified patients that might benefit from replanning. Double-blind evaluation by two radiation oncologists (ROs) was carried out to validate day/week selected for re-planning by the classifier. The cohort was affected by PG mean reduction of 23.7±8.8%. During the first 3weeks, 86.7% cases show PG deformation aligned with predefined tolerance, thus not requiring re-planning. From 4th week, an increased number of pts would potentially benefit from re-planning: a mean of 58% of cases, with an inter-center variability of 8.3%, showed "inadequate" conditions. 11% of cases showed "bias" due to DIR and script failure; 6% showed "warning" output due to potential positioning issues. Comparing re-planning suggested by tool with recommended by ROs, the 4th week seems the most favorable time in 70% cases. SVM and decision-making tool was applied to overcome ART challenges. Pts would benefit from ART and ideal time for re-planning intervention was identified in this retrospective analysis. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  12. Improved tool grinding machine

    DOEpatents

    Dial, C.E. Sr.

    The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thicknesses may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

  13. An open CAM system for dentistry on the basis of China-made 5-axis simultaneous contouring CNC machine tool and industrial CAM software.

    PubMed

    Lu, Li; Liu, Shusheng; Shi, Shenggen; Yang, Jianzhong

    2011-10-01

    China-made 5-axis simultaneous contouring CNC machine tool and domestically developed industrial computer-aided manufacture (CAM) technology were used for full crown fabrication and measurement of crown accuracy, with an attempt to establish an open CAM system for dental processing and to promote the introduction of domestic dental computer-aided design (CAD)/CAM system. Commercially available scanning equipment was used to make a basic digital tooth model after preparation of crown, and CAD software that comes with the scanning device was employed to design the crown by using domestic industrial CAM software to process the crown data in order to generate a solid model for machining purpose, and then China-made 5-axis simultaneous contouring CNC machine tool was used to complete machining of the whole crown and the internal accuracy of the crown internal was measured by using 3D-MicroCT. The results showed that China-made 5-axis simultaneous contouring CNC machine tool in combination with domestic industrial CAM technology can be used for crown making and the crown was well positioned in die. The internal accuracy was successfully measured by using 3D-MicroCT. It is concluded that an open CAM system for dentistry on the basis of China-made 5-axis simultaneous contouring CNC machine tool and domestic industrial CAM software has been established, and development of the system will promote the introduction of domestically-produced dental CAD/CAM system.

  14. Micromechanical Machining Processes and their Application to Aerospace Structures, Devices and Systems

    NASA Technical Reports Server (NTRS)

    Friedrich, Craig R.; Warrington, Robert O.

    1995-01-01

    Micromechanical machining processes are those micro fabrication techniques which directly remove work piece material by either a physical cutting tool or an energy process. These processes are direct and therefore they can help reduce the cost and time for prototype development of micro mechanical components and systems. This is especially true for aerospace applications where size and weight are critical, and reliability and the operating environment are an integral part of the design and development process. The micromechanical machining processes are rapidly being recognized as a complementary set of tools to traditional lithographic processes (such as LIGA) for the fabrication of micromechanical components. Worldwide efforts in the U.S., Germany, and Japan are leading to results which sometimes rival lithography at a fraction of the time and cost. Efforts to develop processes and systems specific to aerospace applications are well underway.

  15. MATC Machine Shop '84: Specific Skill Needs Assessment for Machine Shops in the Milwaukee Area.

    ERIC Educational Resources Information Center

    Roberts, Keith J.

    Building on previous research on the future skill needs of workers in southeastern Wisconsin, a study was conducted at Milwaukee Area Technical College (MATC) to gather information on the machine tool industry in the Milwaukee area. Interviews were conducted by MATC Machine Shop and Tool and Die faculty with representatives from 135 machine shops,…

  16. Machinability of hypereutectic silicon-aluminum alloys

    NASA Astrophysics Data System (ADS)

    Tanaka, T.; Akasawa, T.

    1999-08-01

    The machinability of high-silicon aluminum alloys made by a P/M process and by casting was compared. The cutting test was conducted by turning on lathes with the use of cemented carbide tools. The tool wear by machining the P/M alloy was far smaller than the tool wear by machining the cast alloy. The roughness of the machined surface of the P/M alloy is far better than that of the cast alloy, and the turning speed did not affect it greatly at higher speeds. The P/M alloy produced long chips, so the disposal can cause trouble. The size effect of silicon grains on the machinability is discussed.

  17. The Python Spectral Analysis Tool (PySAT): A Powerful, Flexible, Preprocessing and Machine Learning Library and Interface

    NASA Astrophysics Data System (ADS)

    Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T. G.; Morris, R. V.; Laura, J.; Gaddis, L. R.

    2017-12-01

    Machine learning is a powerful but underutilized approach that can enable planetary scientists to derive meaningful results from the rapidly-growing quantity of available spectral data. For example, regression methods such as Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO), can be used to determine chemical concentrations from ChemCam and SuperCam Laser-Induced Breakdown Spectroscopy (LIBS) data [1]. Many scientists are interested in testing different spectral data processing and machine learning methods, but few have the time or expertise to write their own software to do so. We are therefore developing a free open-source library of software called the Python Spectral Analysis Tool (PySAT) along with a flexible, user-friendly graphical interface to enable scientists to process and analyze point spectral data without requiring significant programming or machine-learning expertise. A related but separately-funded effort is working to develop a graphical interface for orbital data [2]. The PySAT point-spectra tool includes common preprocessing steps (e.g. interpolation, normalization, masking, continuum removal, dimensionality reduction), plotting capabilities, and capabilities to prepare data for machine learning such as creating stratified folds for cross validation, defining training and test sets, and applying calibration transfer so that data collected on different instruments or under different conditions can be used together. The tool leverages the scikit-learn library [3] to enable users to train and compare the results from a variety of multivariate regression methods. It also includes the ability to combine multiple "sub-models" into an overall model, a method that has been shown to improve results and is currently used for ChemCam data [4]. Although development of the PySAT point-spectra tool has focused primarily on the analysis of LIBS spectra, the relevant steps and methods are applicable to any spectral data. The

  18. Prediction of the wear and evolution of cutting tools in a carbide / titanium-aluminum-vanadium machining tribosystem by volumetric tool wear characterization and modeling

    NASA Astrophysics Data System (ADS)

    Kuttolamadom, Mathew Abraham

    The objective of this research work is to create a comprehensive microstructural wear mechanism-based predictive model of tool wear in the tungsten carbide / Ti-6Al-4V machining tribosystem, and to develop a new topology characterization method for worn cutting tools in order to validate the model predictions. This is accomplished by blending first principle wear mechanism models using a weighting scheme derived from scanning electron microscopy (SEM) imaging and energy dispersive x-ray spectroscopy (EDS) analysis of tools worn under different operational conditions. In addition, the topology of worn tools is characterized through scanning by white light interferometry (WLI), and then application of an algorithm to stitch and solidify data sets to calculate the volume of the tool worn away. The methodology was to first combine and weight dominant microstructural wear mechanism models, to be able to effectively predict the tool volume worn away. Then, by developing a new metrology method for accurately quantifying the bulk-3D wear, the model-predicted wear was validated against worn tool volumes obtained from corresponding machining experiments. On analyzing worn crater faces using SEM/EDS, adhesion was found dominant at lower surface speeds, while dissolution wear dominated with increasing speeds -- this is in conformance with the lower relative surface speed requirement for micro welds to form and rupture, essentially defining the mechanical load limit of the tool material. It also conforms to the known dominance of high temperature-controlled wear mechanisms with increasing surface speed, which is known to exponentially increase temperatures especially when machining Ti-6Al-4V due to its low thermal conductivity. Thus, straight tungsten carbide wear when machining Ti-6Al-4V is mechanically-driven at low surface speeds and thermally-driven at high surface speeds. Further, at high surface speeds, craters were formed due to carbon diffusing to the tool surface and

  19. Axiomatic Design and Fabrication of Composite Structures - Applications in Robots, Machine Tools, and Automobiles

    NASA Astrophysics Data System (ADS)

    Lee, Dai Gil; Suh, Nam Pyo

    2005-11-01

    The idea that materials can be designed to satisfy specific performance requirements is relatively new. With high-performance composites, however, the entire process of designing and fabricating a part can be worked out before manufacturing. The purpose of this book is to present an integrated approach to the design and manufacturing of products from advanced composites. It shows how the basic behavior of composites and their constitutive relationships can be used during the design stage, which minimizes the complexity of manufacturing composite parts and reduces the repetitive "design-build-test" cycle. Designing it right the first time is going to determine the competitiveness of a company, the reliability of the part, the robustness of fabrication processes, and ultimately, the cost and development time of composite parts. Most of all, it should expand the use of advanced composite parts in fields that use composites only to a limited extent at this time. To achieve these goals, this book presents the design and fabrication of novel composite parts made for machine tools and other applications like robots and automobiles. This book is suitable as a textbook for graduate courses in the design and fabrication of composites. It will also be of interest to practicing engineers learning about composites and axiomatic design. A CD-ROM is included in every copy of the book, containing Axiomatic CLPT software. This program, developed by the authors, will assist readers in calculating material properties from the microstructure of the composite. This book is part of the Oxford Series on Advanced Manufacturing.

  20. Automatic feed system for ultrasonic machining

    DOEpatents

    Calkins, Noel C.

    1994-01-01

    Method and apparatus for ultrasonic machining in which feeding of a tool assembly holding a machining tool toward a workpiece is accomplished automatically. In ultrasonic machining, a tool located just above a workpiece and vibrating in a vertical direction imparts vertical movement to particles of abrasive material which then remove material from the workpiece. The tool does not contact the workpiece. Apparatus for moving the tool assembly vertically is provided such that it operates with a relatively small amount of friction. Adjustable counterbalance means is provided which allows the tool to be immobilized in its vertical travel. A downward force, termed overbalance force, is applied to the tool assembly. The overbalance force causes the tool to move toward the workpiece as material is removed from the workpiece.

  1. Mathematical support for automated geometry analysis of lathe machining of oblique peakless round-nose tools

    NASA Astrophysics Data System (ADS)

    Filippov, A. V.; Tarasov, S. Yu; Podgornyh, O. A.; Shamarin, N. N.; Filippova, E. O.

    2017-01-01

    Automatization of engineering processes requires developing relevant mathematical support and a computer software. Analysis of metal cutting kinematics and tool geometry is a necessary key task at the preproduction stage. This paper is focused on developing a procedure for determining the geometry of oblique peakless round-nose tool lathe machining with the use of vector/matrix transformations. Such an approach allows integration into modern mathematical software packages in distinction to the traditional analytic description. Such an advantage is very promising for developing automated control of the preproduction process. A kinematic criterion for the applicable tool geometry has been developed from the results of this study. The effect of tool blade inclination and curvature on the geometry-dependent process parameters was evaluated.

  2. The monitoring of transient regimes on machine tools based on speed, acceleration and active electric power absorbed by motors

    NASA Astrophysics Data System (ADS)

    Horodinca, M.

    2016-08-01

    This paper intend to propose some new results related with computer aided monitoring of transient regimes on machine-tools based on the evolution of active electrical power absorbed by the electric motor used to drive the main kinematic chains and the evolution of rotational speed and acceleration of the main shaft. The active power is calculated in numerical format using the evolution of instantaneous voltage and current delivered by electrical power system to the electric motor. The rotational speed and acceleration of the main shaft are calculated based on the signal delivered by a sensor. Three real-time analogic signals are acquired with a very simple computer assisted setup which contains a voltage transformer, a current transformer, an AC generator as rotational speed sensor, a data acquisition system and a personal computer. The data processing and analysis was done using Matlab software. Some different transient regimes were investigated; several important conclusions related with the advantages of this monitoring technique were formulated. Many others features of the experimental setup are also available: to supervise the mechanical loading of machine-tools during cutting processes or for diagnosis of machine-tools condition by active electrical power signal analysis in frequency domain.

  3. Apparatus for correcting precision errors in slide straightness in machine tools

    DOEpatents

    Robinson, Samuel C.; Gerth, Howard L.

    1981-01-01

    The present invention is directed to a mechanism by which small deviations in slideway straightness and roll of a precision machining apparatus may be compensated for. The mechanism of the present invention comprises a fixture support disposed between the slideway carriage and the tool or workpiece fixture and provided with a hinge-like coupling between the carriage and the fixture support so as to allow for the minute and precise displacement of the fixture support in a direction normal to the direction of the slide path so as to readily compensate for slight deviations in the straightness and roll of the slide path.

  4. Apparatus for correcting precision errors in slide straigntness in machine tools

    DOEpatents

    Robinson, S.C.; Gerth, H.L.

    The present invention is directed to a mechanism by which small deviations in slideway straightness and roll of a precision machining apparatus may be compensated for. The mechanism of the present invention comprises a fixture support disposed between the slideway carriage and the tool or workpiece fixture and provided with a hinge-like coupling between the carriage and the fixture support so as to allow for the minute and precise displacement of the fixture support in a direction normal to the direction of the slide path soa as to readily compensate for slight deviations in the straightness and roll of the slide path.

  5. Modeling of tool path for the CNC sheet cutting machines

    NASA Astrophysics Data System (ADS)

    Petunin, Aleksandr A.

    2015-11-01

    In the paper the problem of tool path optimization for CNC (Computer Numerical Control) cutting machines is considered. The classification of the cutting techniques is offered. We also propose a new classification of toll path problems. The tasks of cost minimization and time minimization for standard cutting technique (Continuous Cutting Problem, CCP) and for one of non-standard cutting techniques (Segment Continuous Cutting Problem, SCCP) are formalized. We show that the optimization tasks can be interpreted as discrete optimization problem (generalized travel salesman problem with additional constraints, GTSP). Formalization of some constraints for these tasks is described. For the solution GTSP we offer to use mathematical model of Prof. Chentsov based on concept of a megalopolis and dynamic programming.

  6. A Web Tool for Generating High Quality Machine-readable Biological Pathways.

    PubMed

    Ramirez-Gaona, Miguel; Marcu, Ana; Pon, Allison; Grant, Jason; Wu, Anthony; Wishart, David S

    2017-02-08

    PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events. This palette of entities consists of chemical compounds, proteins, nucleic acids, cellular membranes, subcellular structures, tissues, and organs. All of the visual elements in it can be interactively adjusted and customized. Furthermore, because this tool is a web server, all pathways and pathway elements are publicly accessible. This kind of pathway "crowd sourcing" means that PathWhiz already contains a large and rapidly growing collection of previously drawn pathways and pathway elements. Here we describe a protocol for the quick and easy creation of new pathways and the alteration of existing pathways. To further facilitate pathway editing and creation, the tool contains replication and propagation functions. The replication function allows existing pathways to be used as templates to create or edit new pathways. The propagation function allows one to take an existing pathway and automatically propagate it across different species. Pathways created with this tool can be "re-styled" into different formats (KEGG-like or text-book like), colored with different backgrounds, exported to BioPAX, SBGN-ML, SBML, or PWML data exchange formats, and downloaded as PNG or SVG images. The pathways can easily be incorporated into online databases, integrated into presentations, posters or publications, or used exclusively for online visualization and exploration. This protocol has been successfully applied to

  7. Investigation of Machine-ability of Inconel 800 in EDM with Coated Electrode

    NASA Astrophysics Data System (ADS)

    Karunakaran, K.; Chandrasekaran, M.

    2017-03-01

    The Inconel 800 is a high temperature application alloy which is classified as a nickel based super alloy. It has wide scope in aerospace engineering, gas Turbine etc. The machine-ability studies were found limited on this material. Hence This research focuses on machine-ability studies on EDM of Inconel 800 with Silver Coated Electrolyte Copper Electrode. The purpose of coating on electrode is to reduce tool wear. The factors pulse on Time, Pulse off Time and Peck Current were considered to observe the responses of surface roughness, material removal rate, tool wear rate. Taguchi Full Factorial Design is employed for Design the experiment. Some specific findings were reported and the percentage of contribution of each parameter was furnished

  8. Human factors model concerning the man-machine interface of mining crewstations

    NASA Technical Reports Server (NTRS)

    Rider, James P.; Unger, Richard L.

    1989-01-01

    The U.S. Bureau of Mines is developing a computer model to analyze the human factors aspect of mining machine operator compartments. The model will be used as a research tool and as a design aid. It will have the capability to perform the following: simulated anthropometric or reach assessment, visibility analysis, illumination analysis, structural analysis of the protective canopy, operator fatigue analysis, and computation of an ingress-egress rating. The model will make extensive use of graphics to simplify data input and output. Two dimensional orthographic projections of the machine and its operator compartment are digitized and the data rebuilt into a three dimensional representation of the mining machine. Anthropometric data from either an individual or any size population may be used. The model is intended for use by equipment manufacturers and mining companies during initial design work on new machines. In addition to its use in machine design, the model should prove helpful as an accident investigation tool and for determining the effects of machine modifications made in the field on the critical areas of visibility and control reach ability.

  9. Implementing Machine Learning in the PCWG Tool

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Clifton, Andrew; Ding, Yu; Stuart, Peter

    The Power Curve Working Group (www.pcwg.org) is an ad-hoc industry-led group to investigate the performance of wind turbines in real-world conditions. As part of ongoing experience-sharing exercises, machine learning has been proposed as a possible way to predict turbine performance. This presentation provides some background information about machine learning and how it might be implemented in the PCWG exercises.

  10. Joint properties of a tool machining process to guarantee fluid-proof abilities

    NASA Astrophysics Data System (ADS)

    Bataille, C.; Deltombe, R.; Jourani, A.; Bigerelle, M.

    2017-12-01

    This study addressed the impact of rod surface topography in contact with reciprocating seals. Rods were tooled with and without centreless grinding. All rods tooled with centreless grinding were fluid-proof, in contrast to rods tooled without centreless grinding that either had leaks or were fluid-proof. A method was developed to analyse the machining signature, and the software Mesrug™ was used in order to discriminate roughness parameters that can be used to characterize the sealing functionality. According to this surface roughness analysis, a fluid-proof rod tooled without centreless grinding presents aperiodic large plateaus, and the relevant roughness parameter for characterizing the sealing functionality is the density of summits S DS. Increasing the density of summits counteracts leakage, which may be because motif decomposition integrates three topographical components: circularity (perpendicular long-wave roughness), longitudinal waviness, and roughness thanks to the Wolf pruning algorithm. A 3D analytical contact model was applied to analyse the contact area of each type of sample with the seal surface. This model provides a leakage probability, and the results were consistent with the interpretation of the topographical analysis.

  11. The dynamic analysis of drum roll lathe for machining of rollers

    NASA Astrophysics Data System (ADS)

    Qiao, Zheng; Wu, Dongxu; Wang, Bo; Li, Guo; Wang, Huiming; Ding, Fei

    2014-08-01

    An ultra-precision machine tool for machining of the roller has been designed and assembled, and due to the obvious impact which dynamic characteristic of machine tool has on the quality of microstructures on the roller surface, the dynamic characteristic of the existing machine tool is analyzed in this paper, so is the influence of circumstance that a large scale and slender roller is fixed in the machine on dynamic characteristic of the machine tool. At first, finite element model of the machine tool is built and simplified, and based on that, the paper carries on with the finite element mode analysis and gets the natural frequency and shaking type of four steps of the machine tool. According to the above model analysis results, the weak stiffness systems of machine tool can be further improved and the reasonable bandwidth of control system of the machine tool can be designed. In the end, considering the shock which is caused by Z axis as a result of fast positioning frequently to feeding system and cutting tool, transient analysis is conducted by means of ANSYS analysis in this paper. Based on the results of transient analysis, the vibration regularity of key components of machine tool and its impact on cutting process are explored respectively.

  12. User's manual for tooth contact analysis of face-milled spiral bevel gears with given machine-tool settings

    NASA Technical Reports Server (NTRS)

    Litvin, Faydor L.; Zhang, YI; Chen, Jui-Sheng

    1991-01-01

    Research was performed to develop a computer program that will: (1) simulate the meshing and bearing contact for face milled spiral beval gears with given machine tool settings; and (2) to obtain the output, some of the data is required for hydrodynamic analysis. It is assumed that the machine tool settings and the blank data will be taken from the Gleason summaries. The theoretical aspects of the program are based on 'Local Synthesis and Tooth Contact Analysis of Face Mill Milled Spiral Bevel Gears'. The difference between the computer programs developed herein and the other one is as follows: (1) the mean contact point of tooth surfaces for gears with given machine tool settings must be determined iteratively, while parameters (H and V) are changed (H represents displacement along the pinion axis, V represents the gear displacement that is perpendicular to the plane drawn through the axes of the pinion and the gear of their initial positions), this means that when V differs from zero, the axis of the pionion and the gear are crossed but not intersected; (2) in addition to the regular output data (transmission errors and bearing contact), the new computer program provides information about the contacting force for each contact point and the sliding and the so-called rolling velocity. The following topics are covered: (1) instructions for the users as to how to insert the input data; (2) explanations regarding the output data; (3) numerical example; and (4) listing of the program.

  13. Mathematics for the Workplace. Applications from Machine Tool Technology (Michelin Tire Corporation). A Teacher's Guide.

    ERIC Educational Resources Information Center

    Wallace, Johnny M.; Stewart, Grover

    This module presents a real-world context in which mathematics skills (geometry and trigonometry) are used as part of a daily routine. The context is the machine tool technology field, and the module aims to help students develop the ability to analyze diagrams in order to make mathematical computations. The modules, which features applications…

  14. Study of the Effect of Lubricant Emulsion Percentage and Tool Material on Surface Roughness in Machining of EN-AC 48000 Alloy

    NASA Astrophysics Data System (ADS)

    Soltani, E.; Shahali, H.; Zarepour, H.

    2011-01-01

    In this paper, the effect of machining parameters, namely, lubricant emulsion percentage and tool material on surface roughness has been studied in machining process of EN-AC 48000 aluminum alloy. EN-AC 48000 aluminum alloy is an important alloy in industries. Machining of this alloy is of vital importance due to built-up edge and tool wear. A L9 Taguchi standard orthogonal array has been applied as experimental design to investigate the effect of the factors and their interaction. Nine machining tests have been carried out with three random replications resulting in 27 experiments. Three type of cutting tools including coated carbide (CD1810), uncoated carbide (H10), and polycrystalline diamond (CD10) have been used in this research. Emulsion percentage of lubricant is selected at three levels including 3%, 5% and 10%. Statistical analysis has been employed to study the effect of factors and their interactions using ANOVA method. Moreover, the optimal factors level has been achieved through signal to noise ratio (S/N) analysis. Also, a regression model has been provided to predict the surface roughness. Finally, the results of the confirmation tests have been presented to verify the adequacy of the predictive model. In this research, surface quality was improved by 9% using lubricant and statistical optimization method.

  15. Hybrid test on building structures using electrodynamic fatigue test machine

    NASA Astrophysics Data System (ADS)

    Xu, Zhao-Dong; Wang, Kai-Yang; Guo, Ying-Qing; Wu, Min-Dong; Xu, Meng

    2017-01-01

    Hybrid simulation is an advanced structural dynamic experimental method that combines experimental physical models with analytical numerical models. It has increasingly been recognised as a powerful methodology to evaluate structural nonlinear components and systems under realistic operating conditions. One of the barriers for this advanced testing is the lack of flexible software for hybrid simulation using heterogeneous experimental equipment. In this study, an electrodynamic fatigue test machine is made and a MATLAB program is developed for hybrid simulation. Compared with the servo-hydraulic system, electrodynamic fatigue test machine has the advantages of small volume, easy operation and fast response. A hybrid simulation is conducted to verify the flexibility and capability of the whole system whose experimental substructure is one spring brace and numerical substructure is a two-storey steel frame structure. Experimental and numerical results show the feasibility and applicability of the whole system.

  16. MLBCD: a machine learning tool for big clinical data.

    PubMed

    Luo, Gang

    2015-01-01

    Predictive modeling is fundamental for extracting value from large clinical data sets, or "big clinical data," advancing clinical research, and improving healthcare. Machine learning is a powerful approach to predictive modeling. Two factors make machine learning challenging for healthcare researchers. First, before training a machine learning model, the values of one or more model parameters called hyper-parameters must typically be specified. Due to their inexperience with machine learning, it is hard for healthcare researchers to choose an appropriate algorithm and hyper-parameter values. Second, many clinical data are stored in a special format. These data must be iteratively transformed into the relational table format before conducting predictive modeling. This transformation is time-consuming and requires computing expertise. This paper presents our vision for and design of MLBCD (Machine Learning for Big Clinical Data), a new software system aiming to address these challenges and facilitate building machine learning predictive models using big clinical data. The paper describes MLBCD's design in detail. By making machine learning accessible to healthcare researchers, MLBCD will open the use of big clinical data and increase the ability to foster biomedical discovery and improve care.

  17. Machinability of an experimental Ti-Ag alloy in terms of tool life in a dental CAD/CAM system.

    PubMed

    Inagaki, Ryoichi; Kikuchi, Masafumi; Takahashi, Masatoshi; Takada, Yukyo; Sasaki, Keiichi

    2015-01-01

    Titanium is difficult to machine because of its intrinsic properties. In a previous study, the machinability of titanium was improved by alloying with silver. This study aimed to evaluate the durability of tungsten carbide burs after the fabrication of frameworks using a Ti-20%Ag alloy and titanium with a computer-aided design and computer-aided manufacturing system. There was a significant difference in attrition area ratio between the two metals. Compared with titanium, the ratio of the area of attrition of machining burs was significantly lower for the experimental Ti-20%Ag alloy. The difference in the area of attrition for titanium and Ti-20%Ag became remarkable with increasing number of machining operations. The results show that the same burs can be used for a longer time with Ti-20%Ag than with pure titanium. Therefore, in terms of tool life, the machinability of the Ti-20%Ag alloy is superior to that of titanium.

  18. EQUIPMENT FOR SPARK-ASSISTED MACHINING (OBORUDOVANIE DLYA ELEKTROISKROVOI OBRABOTKI),

    DTIC Science & Technology

    MACHINE TOOLS, * ELECTROEROSIVE MACHINING), MACHINE TOOL INDUSTRY, ELECTROFORMING, ELECTRODES, ELECTROLYTIC CAPACITORS, ELECTRIC DISCHARGES, TOLERANCES(MECHANICS), SURFACE ROUGHNESS, DIES, MOLDINGS, SYNTHETIC FIBERS, USSR

  19. 14. Machine room, building 501, underground structure, May 11, 1956, ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    14. Machine room, building 501, underground structure, May 11, 1956, looking east - Offutt Air Force Base, Strategic Air Command Headquarters & Command Center, Command Center, 901 SAC Boulevard, Bellevue, Sarpy County, NE

  20. Profiles of Major Suppliers to the Automotive Industry : Vol. 7. Machine Tool Suppliers to the Automotive Industry.

    DOT National Transportation Integrated Search

    1982-08-01

    This study summarizes extensive information collected over a two-year period (October 1978 to October 1980) on suppliers of parts and components, materials, and machine tools to the automotive industry in the United States. The objective of the study...

  1. Scattering effects of machined optical surfaces

    NASA Astrophysics Data System (ADS)

    Thompson, Anita Kotha

    1998-09-01

    Optical fabrication is one of the most labor-intensive industries in existence. Lensmakers use pitch to affix glass blanks to metal chucks that hold the glass as they grind it with tools that have not changed much in fifty years. Recent demands placed on traditional optical fabrication processes in terms of surface accuracy, smoothnesses, and cost effectiveness has resulted in the exploitation of precision machining technology to develop a new generation of computer numerically controlled (CNC) optical fabrication equipment. This new kind of precision machining process is called deterministic microgrinding. The most conspicuous feature of optical surfaces manufactured by the precision machining processes (such as single-point diamond turning or deterministic microgrinding) is the presence of residual cutting tool marks. These residual tool marks exhibit a highly structured topography of periodic azimuthal or radial deterministic marks in addition to random microroughness. These distinct topographic features give rise to surface scattering effects that can significantly degrade optical performance. In this dissertation project we investigate the scattering behavior of machined optical surfaces and their imaging characteristics. In particular, we will characterize the residual optical fabrication errors and relate the resulting scattering behavior to the tool and machine parameters in order to evaluate and improve the deterministic microgrinding process. Other desired information derived from the investigation of scattering behavior is the optical fabrication tolerances necessary to satisfy specific image quality requirements. Optical fabrication tolerances are a major cost driver for any precision optical manufacturing technology. The derivation and control of the optical fabrication tolerances necessary for different applications and operating wavelength regimes will play a unique and central role in establishing deterministic microgrinding as a preferred and a

  2. Automated structural classification of lipids by machine learning.

    PubMed

    Taylor, Ryan; Miller, Ryan H; Miller, Ryan D; Porter, Michael; Dalgleish, James; Prince, John T

    2015-03-01

    Modern lipidomics is largely dependent upon structural ontologies because of the great diversity exhibited in the lipidome, but no automated lipid classification exists to facilitate this partitioning. The size of the putative lipidome far exceeds the number currently classified, despite a decade of work. Automated classification would benefit ongoing classification efforts by decreasing the time needed and increasing the accuracy of classification while providing classifications for mass spectral identification algorithms. We introduce a tool that automates classification into the LIPID MAPS ontology of known lipids with >95% accuracy and novel lipids with 63% accuracy. The classification is based upon simple chemical characteristics and modern machine learning algorithms. The decision trees produced are intelligible and can be used to clarify implicit assumptions about the current LIPID MAPS classification scheme. These characteristics and decision trees are made available to facilitate alternative implementations. We also discovered many hundreds of lipids that are currently misclassified in the LIPID MAPS database, strongly underscoring the need for automated classification. Source code and chemical characteristic lists as SMARTS search strings are available under an open-source license at https://www.github.com/princelab/lipid_classifier. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. Nano Mechanical Machining Using AFM Probe

    NASA Astrophysics Data System (ADS)

    Mostofa, Md. Golam

    Complex miniaturized components with high form accuracy will play key roles in the future development of many products, as they provide portability, disposability, lower material consumption in production, low power consumption during operation, lower sample requirements for testing, and higher heat transfer due to their very high surface-to-volume ratio. Given the high market demand for such micro and nano featured components, different manufacturing methods have been developed for their fabrication. Some of the common technologies in micro/nano fabrication are photolithography, electron beam lithography, X-ray lithography and other semiconductor processing techniques. Although these methods are capable of fabricating micro/nano structures with a resolution of less than a few nanometers, some of the shortcomings associated with these methods, such as high production costs for customized products, limited material choices, necessitate the development of other fabricating techniques. Micro/nano mechanical machining, such an atomic force microscope (AFM) probe based nano fabrication, has, therefore, been used to overcome some the major restrictions of the traditional processes. This technique removes material from the workpiece by engaging micro/nano size cutting tool (i.e. AFM probe) and is applicable on a wider range of materials compared to the photolithographic process. In spite of the unique benefits of nano mechanical machining, there are also some challenges with this technique, since the scale is reduced, such as size effects, burr formations, chip adhesions, fragility of tools and tool wear. Moreover, AFM based machining does not have any rotational movement, which makes fabrication of 3D features more difficult. Thus, vibration-assisted machining is introduced into AFM probe based nano mechanical machining to overcome the limitations associated with the conventional AFM probe based scratching method. Vibration-assisted machining reduced the cutting forces

  4. High-efficiency machining methods for aviation materials

    NASA Astrophysics Data System (ADS)

    Kononov, V. K.

    1991-07-01

    The papers contained in this volume present results of theoretical and experimental studies aimed at increasing the efficiency of cutting tools during the machining of high-temperature materials and titanium alloys. Specific topics discussed include a study of the performance of disk cutters during the machining of flexible parts of a high-temperature alloy, VZhL14N; a study of the wear resistance of cutters of hard alloys of various types; effect of a deformed electric field on the precision of the electrochemical machining of gas turbine engine components; and efficient machining of parts of composite materials. The discussion also covers the effect of the technological process structure on the residual stress distribution in the blades of gas turbine engines; modeling of the multiparameter assembly of engineering products for a specified priority of geometrical output parameters; and a study of the quality of the surface and surface layer of specimens machined by a high-temperature pulsed plasma.

  5. Apprentice Machine Theory Outline.

    ERIC Educational Resources Information Center

    Connecticut State Dept. of Education, Hartford. Div. of Vocational-Technical Schools.

    This volume contains outlines for 16 courses in machine theory that are designed for machine tool apprentices. Addressed in the individual course outlines are the following topics: basic concepts; lathes; milling machines; drills, saws, and shapers; heat treatment and metallurgy; grinders; quality control; hydraulics and pneumatics;…

  6. A tool for urban soundscape evaluation applying Support Vector Machines for developing a soundscape classification model.

    PubMed

    Torija, Antonio J; Ruiz, Diego P; Ramos-Ridao, Angel F

    2014-06-01

    To ensure appropriate soundscape management in urban environments, the urban-planning authorities need a range of tools that enable such a task to be performed. An essential step during the management of urban areas from a sound standpoint should be the evaluation of the soundscape in such an area. In this sense, it has been widely acknowledged that a subjective and acoustical categorization of a soundscape is the first step to evaluate it, providing a basis for designing or adapting it to match people's expectations as well. In this sense, this work proposes a model for automatic classification of urban soundscapes. This model is intended for the automatic classification of urban soundscapes based on underlying acoustical and perceptual criteria. Thus, this classification model is proposed to be used as a tool for a comprehensive urban soundscape evaluation. Because of the great complexity associated with the problem, two machine learning techniques, Support Vector Machines (SVM) and Support Vector Machines trained with Sequential Minimal Optimization (SMO), are implemented in developing model classification. The results indicate that the SMO model outperforms the SVM model in the specific task of soundscape classification. With the implementation of the SMO algorithm, the classification model achieves an outstanding performance (91.3% of instances correctly classified). © 2013 Elsevier B.V. All rights reserved.

  7. New numerical approach for the modelling of machining applied to aeronautical structural parts

    NASA Astrophysics Data System (ADS)

    Rambaud, Pierrick; Mocellin, Katia

    2018-05-01

    The manufacturing of aluminium alloy structural aerospace parts involves several steps: forming (rolling, forging …etc), heat treatments and machining. Before machining, the manufacturing processes have embedded residual stresses into the workpiece. The final geometry is obtained during this last step, when up to 90% of the raw material volume is removed by machining. During this operation, the mechanical equilibrium of the part is in constant evolution due to the redistribution of the initial stresses. This redistribution is the main cause for workpiece deflections during machining and for distortions - after unclamping. Both may lead to non-conformity of the part regarding the geometrical and dimensional specifications and therefore to rejection of the part or additional conforming steps. In order to improve the machining accuracy and the robustness of the process, the effect of the residual stresses has to be considered for the definition of the machining process plan and even in the geometrical definition of the part. In this paper, the authors present two new numerical approaches concerning the modelling of machining of aeronautical structural parts. The first deals with the use of an immersed volume framework to model the cutting step, improving the robustness and the quality of the resulting mesh compared to the previous version. The second is about the mechanical modelling of the machining problem. The authors thus show that in the framework of rolled aluminium parts the use of a linear elasticity model is functional in the finite element formulation and promising regarding the reduction of computation times.

  8. CNC machine tool's wear diagnostic and prognostic by using dynamic Bayesian networks

    NASA Astrophysics Data System (ADS)

    Tobon-Mejia, D. A.; Medjaher, K.; Zerhouni, N.

    2012-04-01

    The failure of critical components in industrial systems may have negative consequences on the availability, the productivity, the security and the environment. To avoid such situations, the health condition of the physical system, and particularly of its critical components, can be constantly assessed by using the monitoring data to perform on-line system diagnostics and prognostics. The present paper is a contribution on the assessment of the health condition of a computer numerical control (CNC) tool machine and the estimation of its remaining useful life (RUL). The proposed method relies on two main phases: an off-line phase and an on-line phase. During the first phase, the raw data provided by the sensors are processed to extract reliable features. These latter are used as inputs of learning algorithms in order to generate the models that represent the wear's behavior of the cutting tool. Then, in the second phase, which is an assessment one, the constructed models are exploited to identify the tool's current health state, predict its RUL and the associated confidence bounds. The proposed method is applied on a benchmark of condition monitoring data gathered during several cuts of a CNC tool. Simulation results are obtained and discussed at the end of the paper.

  9. Manufacturing process applications team (MATEAM). [technology transfer in the areas of machine tools and robots

    NASA Technical Reports Server (NTRS)

    1979-01-01

    The transfer of NASA technology to the industrial sector is reported. Presentations to the machine tool and robot industries and direct technology transfers of the Adams Manipulator arm, a-c motor control, and the bolt tension monitor are discussed. A listing of proposed RTOP programs with strong potential is included. A detailed description of the rotor technology available to industry is given.

  10. Machinability of Stellite 6 hardfacing

    NASA Astrophysics Data System (ADS)

    Benghersallah, M.; Boulanouar, L.; Le Coz, G.; Devillez, A.; Dudzinski, D.

    2010-06-01

    This paper reports some experimental findings concerning the machinability at high cutting speed of nickel-base weld-deposited hardfacings for the manufacture of hot tooling. The forging work involves extreme impacts, forces, stresses and temperatures. Thus, mould dies must be extremely resistant. The aim of the project is to create a rapid prototyping process answering to forging conditions integrating a Stellite 6 hardfacing deposed PTA process. This study talks about the dry machining of the hardfacing, using a two tips machining tool and a high speed milling machine equipped by a power consumption recorder Wattpilote. The aim is to show the machinability of the hardfacing, measuring the power and the tip wear by optical microscope and white light interferometer, using different strategies and cutting conditions.

  11. Control/structure interaction conceptual design tool

    NASA Technical Reports Server (NTRS)

    Briggs, Hugh C.

    1990-01-01

    The JPL Control/Structure Interaction Program is developing new analytical methods for designing micro-precision spacecraft with controlled structures. One of these, the Conceptual Design Tool, will illustrate innovative new approaches to the integration of multi-disciplinary analysis and design methods. The tool will be used to demonstrate homogeneity of presentation, uniform data representation across analytical methods, and integrated systems modeling. The tool differs from current 'integrated systems' that support design teams most notably in its support for the new CSI multi-disciplinary engineer. The design tool will utilize a three dimensional solid model of the spacecraft under design as the central data organization metaphor. Various analytical methods, such as finite element structural analysis, control system analysis, and mechanical configuration layout, will store and retrieve data from a hierarchical, object oriented data structure that supports assemblies of components with associated data and algorithms. In addition to managing numerical model data, the tool will assist the designer in organizing, stating, and tracking system requirements.

  12. Diamond Smoothing Tools

    NASA Technical Reports Server (NTRS)

    Voronov, Oleg

    2007-01-01

    Diamond smoothing tools have been proposed for use in conjunction with diamond cutting tools that are used in many finish-machining operations. Diamond machining (including finishing) is often used, for example, in fabrication of precise metal mirrors. A diamond smoothing tool according to the proposal would have a smooth spherical surface. For a given finish machining operation, the smoothing tool would be mounted next to the cutting tool. The smoothing tool would slide on the machined surface left behind by the cutting tool, plastically deforming the surface material and thereby reducing the roughness of the surface, closing microcracks and otherwise generally reducing or eliminating microscopic surface and subsurface defects, and increasing the microhardness of the surface layer. It has been estimated that if smoothing tools of this type were used in conjunction with cutting tools on sufficiently precise lathes, it would be possible to reduce the roughness of machined surfaces to as little as 3 nm. A tool according to the proposal would consist of a smoothing insert in a metal holder. The smoothing insert would be made from a diamond/metal functionally graded composite rod preform, which, in turn, would be made by sintering together a bulk single-crystal or polycrystalline diamond, a diamond powder, and a metallic alloy at high pressure. To form the spherical smoothing tip, the diamond end of the preform would be subjected to flat grinding, conical grinding, spherical grinding using diamond wheels, and finally spherical polishing and/or buffing using diamond powders. If the diamond were a single crystal, then it would be crystallographically oriented, relative to the machining motion, to minimize its wear and maximize its hardness. Spherically polished diamonds could also be useful for purposes other than smoothing in finish machining: They would likely also be suitable for use as heat-resistant, wear-resistant, unlubricated sliding-fit bearing inserts.

  13. Robust iterative learning contouring controller with disturbance observer for machine tool feed drives.

    PubMed

    Simba, Kenneth Renny; Bui, Ba Dinh; Msukwa, Mathew Renny; Uchiyama, Naoki

    2018-04-01

    In feed drive systems, particularly machine tools, a contour error is more significant than the individual axial tracking errors from the view point of enhancing precision in manufacturing and production systems. The contour error must be within the permissible tolerance of given products. In machining complex or sharp-corner products, large contour errors occur mainly owing to discontinuous trajectories and the existence of nonlinear uncertainties. Therefore, it is indispensable to design robust controllers that can enhance the tracking ability of feed drive systems. In this study, an iterative learning contouring controller consisting of a classical Proportional-Derivative (PD) controller and disturbance observer is proposed. The proposed controller was evaluated experimentally by using a typical sharp-corner trajectory, and its performance was compared with that of conventional controllers. The results revealed that the maximum contour error can be reduced by about 37% on average. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

    NASA Astrophysics Data System (ADS)

    Zhu, Kunpeng; Wong, Yoke San; Hong, Geok Soon

    2009-02-01

    In-process monitoring of tool conditions is important in micro-machining due to the high precision requirement and high tool wear rate. Tool condition monitoring in micro-machining poses new challenges compared to conventional machining. In this paper, a multi-category classification approach is proposed for tool flank wear state identification in micro-milling. Continuous Hidden Markov models (HMMs) are adapted for modeling of the tool wear process in micro-milling, and estimation of the tool wear state given the cutting force features. For a noise-robust approach, the HMM outputs are connected via a medium filter to minimize the tool state before entry into the next state due to high noise level. A detailed study on the selection of HMM structures for tool condition monitoring (TCM) is presented. Case studies on the tool state estimation in the micro-milling of pure copper and steel demonstrate the effectiveness and potential of these methods.

  15. Modeling of the flow stress for AISI H13 Tool Steel during Hard Machining Processes

    NASA Astrophysics Data System (ADS)

    Umbrello, Domenico; Rizzuti, Stefania; Outeiro, José C.; Shivpuri, Rajiv

    2007-04-01

    In general, the flow stress models used in computer simulation of machining processes are a function of effective strain, effective strain rate and temperature developed during the cutting process. However, these models do not adequately describe the material behavior in hard machining, where a range of material hardness between 45 and 60 HRC are used. Thus, depending on the specific material hardness different material models must be used in modeling the cutting process. This paper describes the development of a hardness-based flow stress and fracture models for the AISI H13 tool steel, which can be applied for range of material hardness mentioned above. These models were implemented in a non-isothermal viscoplastic numerical model to simulate the machining process for AISI H13 with various hardness values and applying different cutting regime parameters. Predicted results are validated by comparing them with experimental results found in the literature. They are found to predict reasonably well the cutting forces as well as the change in chip morphology from continuous to segmented chip as the material hardness change.

  16. Study of PVD AlCrN Coating for Reducing Carbide Cutting Tool Deterioration in the Machining of Titanium Alloys.

    PubMed

    Cadena, Natalia L; Cue-Sampedro, Rodrigo; Siller, Héctor R; Arizmendi-Morquecho, Ana M; Rivera-Solorio, Carlos I; Di-Nardo, Santiago

    2013-05-24

    The manufacture of medical and aerospace components made of titanium alloys and other difficult-to-cut materials requires the parallel development of high performance cutting tools coated with materials capable of enhanced tribological and resistance properties. In this matter, a thin nanocomposite film made out of AlCrN (aluminum-chromium-nitride) was studied in this research, showing experimental work in the deposition process and its characterization. A heat-treated monolayer coating, competitive with other coatings in the machining of titanium alloys, was analyzed. Different analysis and characterizations were performed on the manufactured coating by scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDXS), and X-ray diffraction (XRD). Furthermore, the mechanical behavior of the coating was evaluated through hardness test and tribology with pin-on-disk to quantify friction coefficient and wear rate. Finally, machinability tests using coated tungsten carbide cutting tools were executed in order to determine its performance through wear resistance, which is a key issue of cutting tools in high-end cutting at elevated temperatures. It was demonstrated that the specimen (with lower friction coefficient than previous research) is more efficient in machinability tests in Ti6Al4V alloys. Furthermore, the heat-treated monolayer coating presented better performance in comparison with a conventional monolayer of AlCrN coating.

  17. Study of PVD AlCrN Coating for Reducing Carbide Cutting Tool Deterioration in the Machining of Titanium Alloys

    PubMed Central

    Cadena, Natalia L.; Cue-Sampedro, Rodrigo; Siller, Héctor R.; Arizmendi-Morquecho, Ana M.; Rivera-Solorio, Carlos I.; Di-Nardo, Santiago

    2013-01-01

    The manufacture of medical and aerospace components made of titanium alloys and other difficult-to-cut materials requires the parallel development of high performance cutting tools coated with materials capable of enhanced tribological and resistance properties. In this matter, a thin nanocomposite film made out of AlCrN (aluminum–chromium–nitride) was studied in this research, showing experimental work in the deposition process and its characterization. A heat-treated monolayer coating, competitive with other coatings in the machining of titanium alloys, was analyzed. Different analysis and characterizations were performed on the manufactured coating by scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDXS), and X-ray diffraction (XRD). Furthermore, the mechanical behavior of the coating was evaluated through hardness test and tribology with pin-on-disk to quantify friction coefficient and wear rate. Finally, machinability tests using coated tungsten carbide cutting tools were executed in order to determine its performance through wear resistance, which is a key issue of cutting tools in high-end cutting at elevated temperatures. It was demonstrated that the specimen (with lower friction coefficient than previous research) is more efficient in machinability tests in Ti6Al4V alloys. Furthermore, the heat-treated monolayer coating presented better performance in comparison with a conventional monolayer of AlCrN coating. PMID:28809266

  18. New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle.

    PubMed

    Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

    2018-01-01

    As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

  19. New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle

    NASA Astrophysics Data System (ADS)

    Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

    2018-01-01

    As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

  20. Developing Parametric Models for the Assembly of Machine Fixtures for Virtual Multiaxial CNC Machining Centers

    NASA Astrophysics Data System (ADS)

    Balaykin, A. V.; Bezsonov, K. A.; Nekhoroshev, M. V.; Shulepov, A. P.

    2018-01-01

    This paper dwells upon a variance parameterization method. Variance or dimensional parameterization is based on sketching, with various parametric links superimposed on the sketch objects and user-imposed constraints in the form of an equation system that determines the parametric dependencies. This method is fully integrated in a top-down design methodology to enable the creation of multi-variant and flexible fixture assembly models, as all the modeling operations are hierarchically linked in the built tree. In this research the authors consider a parameterization method of machine tooling used for manufacturing parts using multiaxial CNC machining centers in the real manufacturing process. The developed method allows to significantly reduce tooling design time when making changes of a part’s geometric parameters. The method can also reduce time for designing and engineering preproduction, in particular, for development of control programs for CNC equipment and control and measuring machines, automate the release of design and engineering documentation. Variance parameterization helps to optimize construction of parts as well as machine tooling using integrated CAE systems. In the framework of this study, the authors demonstrate a comprehensive approach to parametric modeling of machine tooling in the CAD package used in the real manufacturing process of aircraft engines.

  1. Dissipative structures, machines, and organisms: A perspective

    NASA Astrophysics Data System (ADS)

    Kondepudi, Dilip; Kay, Bruce; Dixon, James

    2017-10-01

    Self-organization in nonequilibrium systems resulting in the formation of dissipative structures has been studied in a variety of systems, most prominently in chemical systems. We present a study of a voltage-driven dissipative structure consisting of conducting beads immersed in a viscous medium of oil. In this simple system, we observed remarkably complex organism-like behavior. The dissipative structure consists of a tree structure that spontaneously forms and moves like a worm and exhibits many features characteristic of living organisms. The complex motion of the beads driven by the applied field, the dipole-dipole interaction between the beads, and the hydrodynamic flow of the viscous medium result in a time evolution of the tree structure towards states of lower resistance or higher dissipation and thus higher rates of entropy production. The resulting end-directed evolution manifests as the tree moving to locations seeking higher current, the current that sustains its structure and dynamics. The study of end-directed evolution in the dissipative structure gives us a means to distinguish the fundamental difference between machines and organisms and opens a path for the formulation of physics of organisms.

  2. The Science of and Advanced Technology for Cost-Effective Manufacture of High Precision Engineering Products. Volume 4. Thermal Effects on the Accuracy of Numerically Controlled Machine Tools.

    DTIC Science & Technology

    1985-10-01

    83K0385 FINAL REPORT D Vol. 4 00 THERMAL EFFECTS ON THE ACCURACY OF LD NUME" 1ICALLY CONTROLLED MACHINE TOOLS PREPARED BY I Raghunath Venugopal and M...OF NUMERICALLY CONTROLLED MACHINE TOOLS 12 PERSONAL AJ’HOR(S) Venunorial, Raghunath and M. M. Barash 13a TYPE OF REPORT 13b TIME COVERED 14 DATE OF...TOOLS Prepared by Raghunath Venugopal and M. M. Barash Accesion For Unannounced 0 Justification ........................................... October 1085

  3. Quantum machine learning.

    PubMed

    Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

    2017-09-13

    Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

  4. Quantum machine learning

    NASA Astrophysics Data System (ADS)

    Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

    2017-09-01

    Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

  5. Machinability of titanium metal matrix composites (Ti-MMCs)

    NASA Astrophysics Data System (ADS)

    Aramesh, Maryam

    Titanium metal matrix composites (Ti-MMCs), as a new generation of materials, have various potential applications in aerospace and automotive industries. The presence of ceramic particles enhances the physical and mechanical properties of the alloy matrix. However, the hard and abrasive nature of these particles causes various issues in the field of their machinability. Severe tool wear and short tool life are the most important drawbacks of machining this class of materials. There is very limited work in the literature regarding the machinability of this class of materials especially in the area of tool life estimation and tool wear. By far, polycrystalline diamond (PCD) tools appear to be the best choice for machining MMCs from researchers' point of view. However, due to their high cost, economical alternatives are sought. Cubic boron nitride (CBN) inserts, as the second hardest available tools, show superior characteristics such as great wear resistance, high hardness at elevated temperatures, a low coefficient of friction and a high melting point. Yet, so far CBN tools have not been studied during machining of Ti-MMCs. In this study, a comprehensive study has been performed to explore the tool wear mechanisms of CBN inserts during turning of Ti-MMCs. The unique morphology of the worn faces of the tools was investigated for the first time, which led to new insights in the identification of chemical wear mechanisms during machining of Ti-MMCs. Utilizing the full tool life capacity of cutting tools is also very crucial, due to the considerable costs associated with suboptimal replacement of tools. This strongly motivates development of a reliable model for tool life estimation under any cutting conditions. In this study, a novel model based on the survival analysis methodology is developed to estimate the progressive states of tool wear under any cutting conditions during machining of Ti-MMCs. This statistical model takes into account the machining time in

  6. ASTROS: A multidisciplinary automated structural design tool

    NASA Technical Reports Server (NTRS)

    Neill, D. J.

    1989-01-01

    ASTROS (Automated Structural Optimization System) is a finite-element-based multidisciplinary structural optimization procedure developed under Air Force sponsorship to perform automated preliminary structural design. The design task is the determination of the structural sizes that provide an optimal structure while satisfying numerous constraints from many disciplines. In addition to its automated design features, ASTROS provides a general transient and frequency response capability, as well as a special feature to perform a transient analysis of a vehicle subjected to a nuclear blast. The motivation for the development of a single multidisciplinary design tool is that such a tool can provide improved structural designs in less time than is currently needed. The role of such a tool is even more apparent as modern materials come into widespread use. Balancing conflicting requirements for the structure's strength and stiffness while exploiting the benefits of material anisotropy is perhaps an impossible task without assistance from an automated design tool. Finally, the use of a single tool can bring the design task into better focus among design team members, thereby improving their insight into the overall task.

  7. Membrane proteins structures: A review on computational modeling tools.

    PubMed

    Almeida, Jose G; Preto, Antonio J; Koukos, Panagiotis I; Bonvin, Alexandre M J J; Moreira, Irina S

    2017-10-01

    Membrane proteins (MPs) play diverse and important functions in living organisms. They constitute 20% to 30% of the known bacterial, archaean and eukaryotic organisms' genomes. In humans, their importance is emphasized as they represent 50% of all known drug targets. Nevertheless, experimental determination of their three-dimensional (3D) structure has proven to be both time consuming and rather expensive, which has led to the development of computational algorithms to complement the available experimental methods and provide valuable insights. This review highlights the importance of membrane proteins and how computational methods are capable of overcoming challenges associated with their experimental characterization. It covers various MP structural aspects, such as lipid interactions, allostery, and structure prediction, based on methods such as Molecular Dynamics (MD) and Machine-Learning (ML). Recent developments in algorithms, tools and hybrid approaches, together with the increase in both computational resources and the amount of available data have resulted in increasingly powerful and trustworthy approaches to model MPs. Even though MPs are elementary and important in nature, the determination of their 3D structure has proven to be a challenging endeavor. Computational methods provide a reliable alternative to experimental methods. In this review, we focus on computational techniques to determine the 3D structure of MP and characterize their binding interfaces. We also summarize the most relevant databases and software programs available for the study of MPs. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Assimilating Text-Mining & Bio-Informatics Tools to Analyze Cellulase structures

    NASA Astrophysics Data System (ADS)

    Satyasree, K. P. N. V., Dr; Lalitha Kumari, B., Dr; Jyotsna Devi, K. S. N. V.; Choudri, S. M. Roy; Pratap Joshi, K.

    2017-08-01

    Text-mining is one of the best potential way of automatically extracting information from the huge biological literature. To exploit its prospective, the knowledge encrypted in the text should be converted to some semantic representation such as entities and relations, which could be analyzed by machines. But large-scale practical systems for this purpose are rare. But text mining could be helpful for generating or validating predictions. Cellulases have abundant applications in various industries. Cellulose degrading enzymes are cellulases and the same producing bacteria - Bacillus subtilis & fungus Pseudomonas putida were isolated from top soil of Guntur Dt. A.P. India. Absolute cultures were conserved on potato dextrose agar medium for molecular studies. In this paper, we presented how well the text mining concepts can be used to analyze cellulase producing bacteria and fungi, their comparative structures are also studied with the aid of well-establised, high quality standard bioinformatic tools such as Bioedit, Swissport, Protparam, EMBOSSwin with which a complete data on Cellulases like structure, constituents of the enzyme has been obtained.

  9. Heuristic algorithms for solving of the tool routing problem for CNC cutting machines

    NASA Astrophysics Data System (ADS)

    Chentsov, P. A.; Petunin, A. A.; Sesekin, A. N.; Shipacheva, E. N.; Sholohov, A. E.

    2015-11-01

    The article is devoted to the problem of minimizing the path of the cutting tool to shape cutting machines began. This problem can be interpreted as a generalized traveling salesman problem. Earlier version of the dynamic programming method to solve this problem was developed. Unfortunately, this method allows to process an amount not exceeding thirty circuits. In this regard, the task of constructing quasi-optimal route becomes relevant. In this paper we propose options for quasi-optimal greedy algorithms. Comparison of the results of exact and approximate algorithms is given.

  10. Operating System For Numerically Controlled Milling Machine

    NASA Technical Reports Server (NTRS)

    Ray, R. B.

    1992-01-01

    OPMILL program is operating system for Kearney and Trecker milling machine providing fast easy way to program manufacture of machine parts with IBM-compatible personal computer. Gives machinist "equation plotter" feature, which plots equations that define movements and converts equations to milling-machine-controlling program moving cutter along defined path. System includes tool-manager software handling up to 25 tools and automatically adjusts to account for each tool. Developed on IBM PS/2 computer running DOS 3.3 with 1 MB of random-access memory.

  11. Effect of tool material on machinability of TiCp reinforced Al-1100 composite

    NASA Astrophysics Data System (ADS)

    Harishchandra; Kadadevaramath, R. S.; Anil, K. C.

    2016-09-01

    In present days MMC's are widely used in most of the industries, like automobiles, aerospace, minerals and marine industries, because of its high specific strength to weight ratio. There are many types of reinforcements are available, selection of reinforcement is depends on availability, cost and desired reinforcement properties. In our study Al-1100 is selected as a primary material and Titanium carbide particle (TiCp) of 44 pm size as reinforcement and synthesized by manual stir casting method, by varying the reinforcement percentage. K2DF6 salt was used as wetting agent in order to improve the wetting behaviour of the reinforcement and same was observed in optical micrographs. Further, prepared composite materials are subjected to machinability studies by using lathe tool dynamometer in order to evaluate the cutting force, surface roughness with respect to reinforcement percentage and tool material. From the results, it is observed that the hardness and surface roughness of a specimen increases with the increasing of reinforcement percentage and Hardness of the tool material respectively.

  12. Quality of clinical brain tumor MR spectra judged by humans and machine learning tools.

    PubMed

    Kyathanahally, Sreenath P; Mocioiu, Victor; Pedrosa de Barros, Nuno; Slotboom, Johannes; Wright, Alan J; Julià-Sapé, Margarida; Arús, Carles; Kreis, Roland

    2018-05-01

    To investigate and compare human judgment and machine learning tools for quality assessment of clinical MR spectra of brain tumors. A very large set of 2574 single voxel spectra with short and long echo time from the eTUMOUR and INTERPRET databases were used for this analysis. Original human quality ratings from these studies as well as new human guidelines were used to train different machine learning algorithms for automatic quality control (AQC) based on various feature extraction methods and classification tools. The performance was compared with variance in human judgment. AQC built using the RUSBoost classifier that combats imbalanced training data performed best. When furnished with a large range of spectral and derived features where the most crucial ones had been selected by the TreeBagger algorithm it showed better specificity (98%) in judging spectra from an independent test-set than previously published methods. Optimal performance was reached with a virtual three-class ranking system. Our results suggest that feature space should be relatively large for the case of MR tumor spectra and that three-class labels may be beneficial for AQC. The best AQC algorithm showed a performance in rejecting spectra that was comparable to that of a panel of human expert spectroscopists. Magn Reson Med 79:2500-2510, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  13. Machine learning for the structure-energy-property landscapes of molecular crystals.

    PubMed

    Musil, Félix; De, Sandip; Yang, Jack; Campbell, Joshua E; Day, Graeme M; Ceriotti, Michele

    2018-02-07

    Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol -1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure-property relations in molecular crystal engineering.

  14. Parametric Optimization of Wire Electrical Discharge Machining of Powder Metallurgical Cold Worked Tool Steel using Taguchi Method

    NASA Astrophysics Data System (ADS)

    Sudhakara, Dara; Prasanthi, Guvvala

    2017-04-01

    Wire Cut EDM is an unconventional machining process used to build components of complex shape. The current work mainly deals with optimization of surface roughness while machining P/M CW TOOL STEEL by Wire cut EDM using Taguchi method. The process parameters of the Wire Cut EDM is ON, OFF, IP, SV, WT, and WP. L27 OA is used for to design of the experiments for conducting experimentation. In order to find out the effecting parameters on the surface roughness, ANOVA analysis is engaged. The optimum levels for getting minimum surface roughness is ON = 108 µs, OFF = 63 µs, IP = 11 A, SV = 68 V and WT = 8 g.

  15. Interferometric correction system for a numerically controlled machine

    DOEpatents

    Burleson, Robert R.

    1978-01-01

    An interferometric correction system for a numerically controlled machine is provided to improve the positioning accuracy of a machine tool, for example, for a high-precision numerically controlled machine. A laser interferometer feedback system is used to monitor the positioning of the machine tool which is being moved by command pulses to a positioning system to position the tool. The correction system compares the commanded position as indicated by a command pulse train applied to the positioning system with the actual position of the tool as monitored by the laser interferometer. If the tool position lags the commanded position by a preselected error, additional pulses are added to the pulse train applied to the positioning system to advance the tool closer to the commanded position, thereby reducing the lag error. If the actual tool position is leading in comparison to the commanded position, pulses are deleted from the pulse train where the advance error exceeds the preselected error magnitude to correct the position error of the tool relative to the commanded position.

  16. Machine Translation and Other Translation Technologies.

    ERIC Educational Resources Information Center

    Melby, Alan

    1996-01-01

    Examines the application of linguistic theory to machine translation and translator tools, discusses the use of machine translation and translator tools in the real world of translation, and addresses the impact of translation technology on conceptions of language and other issues. Findings indicate that the human mind is flexible and linguistic…

  17. Efficient production by laser materials processing integrated into metal cutting machines

    NASA Astrophysics Data System (ADS)

    Wiedmaier, M.; Meiners, E.; Dausinger, Friedrich; Huegel, Helmut

    1994-09-01

    Beam guidance of high power YAG-laser (cw, pulsed, Q-switched) with average powers up to 2000 W by flexible glass fibers facilitates the integration of the laser beam as an additional tool into metal cutting machines. Hence, technologies like laser cutting, joining, hardening, caving, structuring of surfaces and laser-marking can be applied directly inside machining centers in one setting, thereby reducing the flow of workpieces resulting in a lowering of costs and production time. Furthermore, materials with restricted machinability--especially hard materials like ceramics, hard metals or sintered alloys--can be shaped by laser-caving or laser assisted machining. Altogether, the flexibility of laser integrated machining centers is substantially increased or the efficiency of a production line is raised by time-savings or extended feasibilities with techniques like hardening, welding or caving.

  18. A vibro-haptic human-machine interface for structural health monitoring

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mascarenas, David; Plont, Crystal; Brown, Christina

    The structural health monitoring (SHM) community’s goal has been to endow physical systems with a nervous system not unlike those commonly found in living organisms. Typically the SHM community has attempted to do this by instrumenting structures with a variety of sensors, and then applying various signal processing and classification procedures to the data in order to detect the presence of damage, the location of damage, the severity of damage, and to estimate the remaining useful life of the structure. This procedure has had some success, but we are still a long way from achieving the performance of nervous systemsmore » found in biology. This is primarily because contemporary classification algorithms do not have the performance required. In many cases expert judgment is superior to automated classification. This work introduces a new paradigm. We propose interfacing the human nervous system to the distributed sensor network located on the structure and developing new techniques to enable human-machine cooperation. Results from the field of sensory substitution suggest this should be possible. This study investigates a vibro-haptic human-machine interface for SHM. The investigation was performed using a surrogate three-story structure. The structure features three nonlinearity-inducing bumpers to simulate damage. Accelerometers are placed on each floor to measure the response of the structure to a harmonic base excitation. The accelerometer measurements are preprocessed. As a result, the preprocessed data is then encoded encoded as a vibro-tactile stimulus. Human subjects were then subjected to the vibro-tactile stimulus and asked to characterize the damage in the structure.« less

  19. A vibro-haptic human-machine interface for structural health monitoring

    DOE PAGES

    Mascarenas, David; Plont, Crystal; Brown, Christina; ...

    2014-11-01

    The structural health monitoring (SHM) community’s goal has been to endow physical systems with a nervous system not unlike those commonly found in living organisms. Typically the SHM community has attempted to do this by instrumenting structures with a variety of sensors, and then applying various signal processing and classification procedures to the data in order to detect the presence of damage, the location of damage, the severity of damage, and to estimate the remaining useful life of the structure. This procedure has had some success, but we are still a long way from achieving the performance of nervous systemsmore » found in biology. This is primarily because contemporary classification algorithms do not have the performance required. In many cases expert judgment is superior to automated classification. This work introduces a new paradigm. We propose interfacing the human nervous system to the distributed sensor network located on the structure and developing new techniques to enable human-machine cooperation. Results from the field of sensory substitution suggest this should be possible. This study investigates a vibro-haptic human-machine interface for SHM. The investigation was performed using a surrogate three-story structure. The structure features three nonlinearity-inducing bumpers to simulate damage. Accelerometers are placed on each floor to measure the response of the structure to a harmonic base excitation. The accelerometer measurements are preprocessed. As a result, the preprocessed data is then encoded encoded as a vibro-tactile stimulus. Human subjects were then subjected to the vibro-tactile stimulus and asked to characterize the damage in the structure.« less

  20. The Security of Machine Learning

    DTIC Science & Technology

    2008-04-24

    Machine learning has become a fundamental tool for computer security, since it can rapidly evolve to changing and complex situations. That...adaptability is also a vulnerability: attackers can exploit machine learning systems. We present a taxonomy identifying and analyzing attacks against machine ...We use our framework to survey and analyze the literature of attacks against machine learning systems. We also illustrate our taxonomy by showing

  1. Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students.

    PubMed

    Khumrin, Piyapong; Ryan, Anna; Judd, Terry; Verspoor, Karin

    2017-01-01

    Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is both critical and challenging. In this paper, we describe the development of a machine learning model to support medical students' diagnostic decisions. Machine learning models were trained on 208 clinical cases presenting with abdominal pain, to predict five diagnoses. We assessed which of these models are likely to be most effective for use in an e-learning tool that allows students to interact with a virtual patient. The broader goal is to utilise these models to generate personalised feedback based on the specific patient information requested by students and their active diagnostic hypotheses.

  2. A Review on High-Speed Machining of Titanium Alloys

    NASA Astrophysics Data System (ADS)

    Rahman, Mustafizur; Wang, Zhi-Gang; Wong, Yoke-San

    Titanium alloys have been widely used in the aerospace, biomedical and automotive industries because of their good strength-to-weight ratio and superior corrosion resistance. However, it is very difficult to machine them due to their poor machinability. When machining titanium alloys with conventional tools, the tool wear rate progresses rapidly, and it is generally difficult to achieve a cutting speed of over 60m/min. Other types of tool materials, including ceramic, diamond, and cubic boron nitride (CBN), are highly reactive with titanium alloys at higher temperature. However, binder-less CBN (BCBN) tools, which do not have any binder, sintering agent or catalyst, have a remarkably longer tool life than conventional CBN inserts even at high cutting speeds. In order to get deeper understanding of high speed machining (HSM) of titanium alloys, the generation of mathematical models is essential. The models are also needed to predict the machining parameters for HSM. This paper aims to give an overview of recent developments in machining and HSM of titanium alloys, geometrical modeling of HSM, and cutting force models for HSM of titanium alloys.

  3. lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine.

    PubMed

    Sun, Lei; Liu, Hui; Zhang, Lin; Meng, Jia

    2015-01-01

    Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.

  4. Integrated modeling and analysis of the multiple electromechanical couplings for the direct driven feed system in machine tools

    NASA Astrophysics Data System (ADS)

    Yang, Xiaojun; Lu, Dun; Liu, Hui; Zhao, Wanhua

    2018-06-01

    The complicated electromechanical coupling phenomena due to different kinds of causes have significant influences on the dynamic precision of the direct driven feed system in machine tools. In this paper, a novel integrated modeling and analysis method of the multiple electromechanical couplings for the direct driven feed system in machine tools is presented. At first, four different kinds of electromechanical coupling phenomena in the direct driven feed system are analyzed systematically. Then a novel integrated modeling and analysis method of the electromechanical coupling which is influenced by multiple factors is put forward. In addition, the effects of multiple electromechanical couplings on the dynamic precision of the feed system and their main influencing factors are compared and discussed, respectively. Finally, the results of modeling and analysis are verified by the experiments. It finds out that multiple electromechanical coupling loops, which are overlapped and influenced by each other, are the main reasons of the displacement fluctuations in the direct driven feed system.

  5. Crystalline molecular machines: Encoding supramolecular dynamics into molecular structure

    PubMed Central

    Garcia-Garibay, Miguel A.

    2005-01-01

    Crystalline molecular machines represent an exciting new branch of crystal engineering and materials science with important implications to nanotechnology. Crystalline molecular machines are crystals built with molecules that are structurally programmed to respond collectively to mechanic, electric, magnetic, or photonic stimuli to fulfill specific functions. One of the main challenges in their construction derives from the picometric precision required for their mechanic operation within the close-packed, self-assembled environment of crystalline solids. In this article, we outline some of the general guidelines for their design and apply them for the construction of molecular crystals with units intended to emulate macroscopic gyroscopes and compasses. Recent advances in the preparation, crystallization, and dynamic characterization of these interesting systems offer a foothold to the possibilities and help highlight some avenues for future experimentation. PMID:16046543

  6. RNA-SSPT: RNA Secondary Structure Prediction Tools.

    PubMed

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

  7. RNA-SSPT: RNA Secondary Structure Prediction Tools

    PubMed Central

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes. PMID:24250115

  8. SU-F-T-459: ArcCHECK Machine QA : Highly Efficient Quality Assurance Tool for VMAT, SRS & SBRT Linear Accelerator Delivery

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mhatre, V; Patwe, P; Dandekar, P

    Purpose: Quality assurance (QA) of complex linear accelerators is critical and highly time consuming. ArcCHECK Machine QA tool is used to test geometric and delivery aspects of linear accelerator. In this study we evaluated the performance of this tool. Methods: Machine QA feature allows user to perform quality assurance tests using ArcCHECK phantom. Following tests were performed 1) Gantry Speed 2) Gantry Rotation 3) Gantry Angle 4)MLC/Collimator QA 5)Beam Profile Flatness & Symmetry. Data was collected on trueBEAM stX machine for 6 MV for a period of one year. The Gantry QA test allows to view errors in gantry angle,more » rotation & assess how accurately the gantry moves around the isocentre. The MLC/Collimator QA tool is used to analyze & locate the differences between leaf bank & jaw position of linac. The flatness & Symmetry test quantifies beam flatness & symmetry in IEC-y & x direction. The Gantry & Flatness/Symmetry test can be performed for static & dynamic delivery. Results: The Gantry speed was 3.9 deg/sec with speed maximum deviation around 0.3 deg/sec. The Gantry Isocentre for arc delivery was 0.9mm & static delivery was 0.4mm. The maximum percent positive & negative difference was found to be 1.9 % & – 0.25 % & maximum distance positive & negative diff was 0.4mm & – 0.3 mm for MLC/Collimator QA. The Flatness for Arc delivery was 1.8 % & Symmetry for Y was 0.8 % & X was 1.8 %. The Flatness for gantry 0°,270°,90° & 180° was 1.75,1.9,1.8 & 1.6% respectively & Symmetry for X & Y was 0.8,0.6% for 0°, 0.6,0.7% for 270°, 0.6,1% for 90° & 0.6,0.7% for 180°. Conclusion: ArcCHECK Machine QA is an useful tool for QA of Modern linear accelerators as it tests both geometric & delivery aspects. This is very important for VMAT, SRS & SBRT treatments.« less

  9. A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

    PubMed Central

    Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.

    2014-01-01

    Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953

  10. A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.

    PubMed

    Sweeney, Elizabeth M; Vogelstein, Joshua T; Cuzzocreo, Jennifer L; Calabresi, Peter A; Reich, Daniel S; Crainiceanu, Ciprian M; Shinohara, Russell T

    2014-01-01

    Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.

  11. High-precision micro/nano-scale machining system

    DOEpatents

    Kapoor, Shiv G.; Bourne, Keith Allen; DeVor, Richard E.

    2014-08-19

    A high precision micro/nanoscale machining system. A multi-axis movement machine provides relative movement along multiple axes between a workpiece and a tool holder. A cutting tool is disposed on a flexible cantilever held by the tool holder, the tool holder being movable to provide at least two of the axes to set the angle and distance of the cutting tool relative to the workpiece. A feedback control system uses measurement of deflection of the cantilever during cutting to maintain a desired cantilever deflection and hence a desired load on the cutting tool.

  12. The Python Spectral Analysis Tool (PySAT) for Powerful, Flexible, and Easy Preprocessing and Machine Learning with Point Spectral Data

    NASA Astrophysics Data System (ADS)

    Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T.; Morris, R. V.; Laura, J.

    2018-04-01

    The PySAT point spectra tool provides a flexible graphical interface, enabling scientists to apply a wide variety of preprocessing and machine learning methods to point spectral data, with an emphasis on multivariate regression.

  13. Toward Intelligent Machine Learning Algorithms

    DTIC Science & Technology

    1988-05-01

    Machine learning is recognized as a tool for improving the performance of many kinds of systems, yet most machine learning systems themselves are not...directed systems, and with the addition of a knowledge store for organizing and maintaining knowledge to assist learning, a learning machine learning (L...ML) algorithm is possible. The necessary components of L-ML systems are presented along with several case descriptions of existing machine learning systems

  14. Importance of polarity change in the electrical discharge machining

    NASA Astrophysics Data System (ADS)

    Schulze, H.-P.

    2017-10-01

    The polarity change in the electrical discharge machining is still a problem and is often performed completely unmotivated or randomly. The polarity must be designated primarily, i.e. the anodic part must be clearly assigned to the tool or the workpiece. Normally, the polarity of the workpiece electrode is named. In paper, will be shown which determine fundamental causes the structural behavior of the cathode and anode, and when it makes sense to change the polarity. The polarity change is primarily dependent on the materials that are used as cathode and anode. This distinction must be made if there are pure metals or complex materials. Secondary of the polarity change is also affected by the process energy source (PES) and the supply line. The polarity change is mostly influenced by the fact that the removal is to be maximized on the workpiece while the tool is minimal removal (wear) occur. A second factor that makes a polarity change needed is the use of electrical discharge in combination with other machining methods, such as electrochemical machining (ECM).

  15. Drilling Machines: Vocational Machine Shop.

    ERIC Educational Resources Information Center

    Thomas, John C.

    The lessons and supportive information in this field tested instructional block provide a guide for teachers in developing a machine shop course of study in drilling. The document is comprised of operation sheets, information sheets, and transparency masters for 23 lessons. Each lesson plan includes a performance objective, material and tools,…

  16. Drilling High Precision Holes in Ti6Al4V Using Rotary Ultrasonic Machining and Uncertainties Underlying Cutting Force, Tool Wear, and Production Inaccuracies.

    PubMed

    Chowdhury, M A K; Sharif Ullah, A M M; Anwar, Saqib

    2017-09-12

    Ti6Al4V alloys are difficult-to-cut materials that have extensive applications in the automotive and aerospace industry. A great deal of effort has been made to develop and improve the machining operations of Ti6Al4V alloys. This paper presents an experimental study that systematically analyzes the effects of the machining conditions (ultrasonic power, feed rate, spindle speed, and tool diameter) on the performance parameters (cutting force, tool wear, overcut error, and cylindricity error), while drilling high precision holes on the workpiece made of Ti6Al4V alloys using rotary ultrasonic machining (RUM). Numerical results were obtained by conducting experiments following the design of an experiment procedure. The effects of the machining conditions on each performance parameter have been determined by constructing a set of possibility distributions (i.e., trapezoidal fuzzy numbers) from the experimental data. A possibility distribution is a probability-distribution-neural representation of uncertainty, and is effective in quantifying the uncertainty underlying physical quantities when there is a limited number of data points which is the case here. Lastly, the optimal machining conditions have been identified using these possibility distributions.

  17. Chatter active control in a lathe machine using magnetostrictive actuator

    NASA Astrophysics Data System (ADS)

    Nosouhi, R.; Behbahani, S.

    2011-01-01

    This paper analyzes the chatter phenomena in lathe machines. Chatter is one of the main causes of inaccuracy, reduction of life cycle of the machine and tool wear in machine tools. This phenomenon limits the depth of cut as a function of the cutting speed, which consequently reduces the material removal rate and machining efficiency. Chatter control is therefore important since it increases the stability region in machining and increases the critical depth of cut in machining case. To control the chatter in lathe machines, a magnetostrictive actuator is used. The materials with magnetostriction properties are kind of smart materials of which their length changes as a result of applying an exterior magnetic field, which make them suitable for control applications. It is assumed that the actuator applies the proper force exactly at the point where the machining force is applied on the tool. In this paper the chatter stability lobes is excelled as a result of applying a PID controller on the magnetostrictive actuator equipped-tool in turning.

  18. Tool vibration detection with eddy current sensors in machining process and computation of stability lobes using fuzzy classifiers

    NASA Astrophysics Data System (ADS)

    Devillez, Arnaud; Dudzinski, Daniel

    2007-01-01

    Today the knowledge of a process is very important for engineers to find optimal combination of control parameters warranting productivity, quality and functioning without defects and failures. In our laboratory, we carry out research in the field of high speed machining with modelling, simulation and experimental approaches. The aim of our investigation is to develop a software allowing the cutting conditions optimisation to limit the number of predictive tests, and the process monitoring to prevent any trouble during machining operations. This software is based on models and experimental data sets which constitute the knowledge of the process. In this paper, we deal with the problem of vibrations occurring during a machining operation. These vibrations may cause some failures and defects to the process, like workpiece surface alteration and rapid tool wear. To measure on line the tool micro-movements, we equipped a lathe with a specific instrumentation using eddy current sensors. Obtained signals were correlated with surface finish and a signal processing algorithm was used to determine if a test is stable or unstable. Then, a fuzzy classification method was proposed to classify the tests in a space defined by the width of cut and the cutting speed. Finally, it was shown that the fuzzy classification takes into account of the measurements incertitude to compute the stability limit or stability lobes of the process.

  19. Dual linear structured support vector machine tracking method via scale correlation filter

    NASA Astrophysics Data System (ADS)

    Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

    2018-01-01

    Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

  20. Review of "Conceptual Structures: Information Processing in Mind and Machine."

    ERIC Educational Resources Information Center

    Smoliar, Stephen W.

    This review of the book, "Conceptual Structures: Information Processing in Mind and Machine," by John F. Sowa, argues that anyone who plans to get involved with issues of knowledge representation should have at least a passing acquaintance with Sowa's conceptual graphs for a database interface. (Used to model the underlying semantics of…

  1. Hard turning micro-machine tool

    DOEpatents

    DeVor, Richard E; Adair, Kurt; Kapoor, Shiv G

    2013-10-22

    A micro-scale apparatus for supporting a tool for hard turning comprises a base, a pivot coupled to the base, an actuator coupled to the base, and at least one member coupled to the actuator at one end and rotatably coupled to the pivot at another end. A tool mount is disposed on the at least one member. The at least one member defines a first lever arm between the pivot and the tool mount, and a second lever arm between the pivot and the actuator. The first lever arm has a length that is less than a length of the second lever arm. The actuator moves the tool mount along an arc.

  2. Modeling and simulation of five-axis virtual machine based on NX

    NASA Astrophysics Data System (ADS)

    Li, Xiaoda; Zhan, Xianghui

    2018-04-01

    Virtual technology in the machinery manufacturing industry has shown the role of growing. In this paper, the Siemens NX software is used to model the virtual CNC machine tool, and the parameters of the virtual machine are defined according to the actual parameters of the machine tool so that the virtual simulation can be carried out without loss of the accuracy of the simulation. How to use the machine builder of the CAM module to define the kinematic chain and machine components of the machine is described. The simulation of virtual machine can provide alarm information of tool collision and over cutting during the process to users, and can evaluate and forecast the rationality of the technological process.

  3. Safety issues in high speed machining

    NASA Astrophysics Data System (ADS)

    1994-05-01

    There are several risks related to High-Speed Milling, but they have not been systematically determined or studied so far. Increased loads by high centrifugal forces may result in dramatic hazards. Flying tools or fragments from a tool with high kinetic energy may damage surrounding people, machines and devices. In the project, mechanical risks were evaluated, theoretic values for kinetic energies of rotating tools were calculated, possible damages of the flying objects were determined and terms to eliminate the risks were considered. The noise levels of the High-Speed Machining center owned by the Helsinki University of Technology (HUT) and the Technical Research Center of Finland (VTT) in practical machining situation were measured and the results were compared to those after basic preventive measures were taken.

  4. Introduction to Machine Tool Technology, Machine Shop Work--Intermediate: 9555.01.

    ERIC Educational Resources Information Center

    Dade County Public Schools, Miami, FL.

    The course outline has been prepared as a guide to assist the instructor to plan systematically and to present meaningful lessons programmed to meet the necessary training needed by the machine shop student. A beginning course, the four blocks of instruction contained in the outline are designed to enable the student to obtain the manipulative…

  5. Foam-machining tool with eddy-current transducer

    NASA Technical Reports Server (NTRS)

    Copper, W. P.

    1975-01-01

    Three-cutter machining system for foam-covered tanks incorporates eddy-current sensor. Sensor feeds signal to numerical controller which programs rotational and vertical axes of sensor travel, enabling cutterhead to profile around tank protrusions.

  6. Articulated, Performance-Based Instruction Objectives Guide for Machine Shop Technology.

    ERIC Educational Resources Information Center

    Henderson, William Edward, Jr., Ed.

    This articulation guide contains 21 units of instruction for two years of machine shop. The objectives of the program are to provide the student with the basic terminology and fundamental knowledge and skills in machining (year 1) and to teach him/her to set up and operate machine tools and make or repair metal parts, tools, and machines (year 2).…

  7. Grid Stiffened Structure Analysis Tool

    NASA Technical Reports Server (NTRS)

    1999-01-01

    The Grid Stiffened Analysis Tool contract is contract performed by Boeing under NASA purchase order H30249D. The contract calls for a "best effort" study comprised of two tasks: (1) Create documentation for a composite grid-stiffened structure analysis tool, in the form of a Microsoft EXCEL spread sheet, that was developed by originally at Stanford University and later further developed by the Air Force, and (2) Write a program that functions as a NASTRAN pre-processor to generate an FEM code for grid-stiffened structure. In performing this contract, Task 1 was given higher priority because it enables NASA to make efficient use of a unique tool they already have; Task 2 was proposed by Boeing because it also would be beneficial to the analysis of composite grid-stiffened structures, specifically in generating models for preliminary design studies. The contract is now complete, this package includes copies of the user's documentation for Task 1 and a CD ROM & diskette with an electronic copy of the user's documentation and an updated version of the "GRID 99" spreadsheet.

  8. Laser assisted machining: a state of art review

    NASA Astrophysics Data System (ADS)

    Punugupati, Gurabvaiah; Kandi, Kishore Kumar; Bose, P. S. C.; Rao, C. S. P.

    2016-09-01

    Difficult-to-cut materials have increasing demand in aerospace and automobile industries due to their high yield stress, high strength to weight ratio, high toughness, high wear resistance, high creep, high corrosion resistivity, ability to retain high strength at high temperature, etc. The machinability of these advanced materials, using conventional methods of machining is typical due to the high temperature and pressure at the cutting zone and tool and properties such as low thermal conductivity, high cutting forces and cutting temperatures makes the materials difficult to machine. Laser assisted machining (LAM) is a new and innovative technique for machining the difficult-to-cut materials. This paper deals with a review on the advances in lasers, tools and the mechanism of machining using LAM and their effects.

  9. Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

    PubMed

    Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

    2002-01-01

    Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

  10. Drilling of optical glass with electroplated diamond tools

    NASA Astrophysics Data System (ADS)

    Wang, A. J.; Luan, C. G.; Yu, A. B.

    2010-10-01

    K9 optical glass drilling experiments were carried out. Bright nickel electroplated diamond tools with small slots and under heat treatment in different temperature were fabricated. Scan electro microscope was applied to analyze the wear of electroplated diamond tool. The material removal rate and grinding ratio were calculated. Machining quality was observed. Bond coating hardness was measured. The experimental results show that coolant is needed for the drilling processes of optical glasses. Heat treatment temperature of diamond tool has influence on wearability of diamond tool and grinding ratio. There were two wear types of electroplated diamond tool, diamond grit wear and bond wear. With the machining processes, wear of diamond grits included fracture, blunt and pull-out, and electroplated bond was gradually worn out. High material removal rates could be obtained by using diamond tool with suitable slot numbers. Bright nickel coating bond presents smallest grains and has better mechanical properties. Bright nickel electroplated diamond tool with slot structure and heat treatment under 200°C was suitable for optical glass drilling.

  11. Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

    PubMed

    Bisenius, Sandrine; Mueller, Karsten; Diehl-Schmid, Janine; Fassbender, Klaus; Grimmer, Timo; Jessen, Frank; Kassubek, Jan; Kornhuber, Johannes; Landwehrmeyer, Bernhard; Ludolph, Albert; Schneider, Anja; Anderl-Straub, Sarah; Stuke, Katharina; Danek, Adrian; Otto, Markus; Schroeter, Matthias L

    2017-01-01

    Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with

  12. Purely Structural Protein Scoring Functions Using Support Vector Machine and Ensemble Learning.

    PubMed

    Mirzaei, Shokoufeh; Sidi, Tomer; Keasar, Chen; Crivelli, Silvia

    2016-08-24

    The function of a protein is determined by its structure, which creates a need for efficient methods of protein structure determination to advance scientific and medical research. Because current experimental structure determination methods carry a high price tag, computational predictions are highly desirable. Given a protein sequence, computational methods produce numerous 3D structures known as decoys. However, selection of the best quality decoys is challenging as the end users can handle only a few ones. Therefore, scoring functions are central to decoy selection. They combine measurable features into a single number indicator of decoy quality. Unfortunately, current scoring functions do not consistently select the best decoys. Machine learning techniques offer great potential to improve decoy scoring. This paper presents two machine-learning based scoring functions to predict the quality of proteins structures, i.e., the similarity between the predicted structure and the experimental one without knowing the latter. We use different metrics to compare these scoring functions against three state-of-the-art scores. This is a first attempt at comparing different scoring functions using the same non-redundant dataset for training and testing and the same features. The results show that adding informative features may be more significant than the method used.

  13. Positional reference system for ultraprecision machining

    DOEpatents

    Arnold, Jones B.; Burleson, Robert R.; Pardue, Robert M.

    1982-01-01

    A stable positional reference system for use in improving the cutting tool-to-part contour position in numerical controlled-multiaxis metal turning machines is provided. The reference system employs a plurality of interferometers referenced to orthogonally disposed metering bars which are substantially isolated from machine strain induced position errors for monitoring the part and tool positions relative to the metering bars. A microprocessor-based control system is employed in conjunction with the plurality of position interferometers and part contour description data inputs to calculate error components for each axis of movement and output them to corresponding axis drives with appropriate scaling and error compensation. Real-time position control, operating in combination with the reference system, makes possible the positioning of the cutting points of a tool along a part locus with a substantially greater degree of accuracy than has been attained previously in the art by referencing and then monitoring only the tool motion relative to a reference position located on the machine base.

  14. Positional reference system for ultraprecision machining

    DOEpatents

    Arnold, J.B.; Burleson, R.R.; Pardue, R.M.

    1980-09-12

    A stable positional reference system for use in improving the cutting tool-to-part contour position in numerical controlled-multiaxis metal turning machines is provided. The reference system employs a plurality of interferometers referenced to orthogonally disposed metering bars which are substantially isolated from machine strain induced position errors for monitoring the part and tool positions relative to the metering bars. A microprocessor-based control system is employed in conjunction with the plurality of positions interferometers and part contour description data input to calculate error components for each axis of movement and output them to corresponding axis driven with appropriate scaling and error compensation. Real-time position control, operating in combination with the reference system, makes possible the positioning of the cutting points of a tool along a part locus with a substantially greater degree of accuracy than has been attained previously in the art by referencing and then monitoring only the tool motion relative to a reference position located on the machine base.

  15. Classification and assessment tools for structural motif discovery algorithms.

    PubMed

    Badr, Ghada; Al-Turaiki, Isra; Mathkour, Hassan

    2013-01-01

    Motif discovery is the problem of finding recurring patterns in biological data. Patterns can be sequential, mainly when discovered in DNA sequences. They can also be structural (e.g. when discovering RNA motifs). Finding common structural patterns helps to gain a better understanding of the mechanism of action (e.g. post-transcriptional regulation). Unlike DNA motifs, which are sequentially conserved, RNA motifs exhibit conservation in structure, which may be common even if the sequences are different. Over the past few years, hundreds of algorithms have been developed to solve the sequential motif discovery problem, while less work has been done for the structural case. In this paper, we survey, classify, and compare different algorithms that solve the structural motif discovery problem, where the underlying sequences may be different. We highlight their strengths and weaknesses. We start by proposing a benchmark dataset and a measurement tool that can be used to evaluate different motif discovery approaches. Then, we proceed by proposing our experimental setup. Finally, results are obtained using the proposed benchmark to compare available tools. To the best of our knowledge, this is the first attempt to compare tools solely designed for structural motif discovery. Results show that the accuracy of discovered motifs is relatively low. The results also suggest a complementary behavior among tools where some tools perform well on simple structures, while other tools are better for complex structures. We have classified and evaluated the performance of available structural motif discovery tools. In addition, we have proposed a benchmark dataset with tools that can be used to evaluate newly developed tools.

  16. Use of machine learning methods to classify Universities based on the income structure

    NASA Astrophysics Data System (ADS)

    Terlyga, Alexandra; Balk, Igor

    2017-10-01

    In this paper we discuss use of machine learning methods such as self organizing maps, k-means and Ward’s clustering to perform classification of universities based on their income. This classification will allow us to quantitate classification of universities as teaching, research, entrepreneur, etc. which is important tool for government, corporations and general public alike in setting expectation and selecting universities to achieve different goals.

  17. Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging.

    PubMed

    Falahati, Farshad; Westman, Eric; Simmons, Andrew

    2014-01-01

    Machine learning algorithms and multivariate data analysis methods have been widely utilized in the field of Alzheimer's disease (AD) research in recent years. Advances in medical imaging and medical image analysis have provided a means to generate and extract valuable neuroimaging information. Automatic classification techniques provide tools to analyze this information and observe inherent disease-related patterns in the data. In particular, these classifiers have been used to discriminate AD patients from healthy control subjects and to predict conversion from mild cognitive impairment to AD. In this paper, recent studies are reviewed that have used machine learning and multivariate analysis in the field of AD research. The main focus is on studies that used structural magnetic resonance imaging (MRI), but studies that included positron emission tomography and cerebrospinal fluid biomarkers in addition to MRI are also considered. A wide variety of materials and methods has been employed in different studies, resulting in a range of different outcomes. Influential factors such as classifiers, feature extraction algorithms, feature selection methods, validation approaches, and cohort properties are reviewed, as well as key MRI-based and multi-modal based studies. Current and future trends are discussed.

  18. Finite Element Structural Analysis of a Low Energy Micro Sheet Forming Machine Concept Design

    NASA Astrophysics Data System (ADS)

    Razali, A. R.; Ann, C. T.; Ahmad, A. F.; Shariff, H. M.; Kasim, N. I.; Musa, M. A.

    2017-05-01

    It is forecasted that with the miniaturization of materials being processed, energy consumption will also be ‘miniaturized’ proportionally. The aim of this researchis to design a low energy micro-sheet-forming machine for the application of thin sheet metal. A fewconcept designsof machine structure were produced. With the help of FE software, the structure is then subjected to a forming force to observe deflection in the structure for the selection of the best and simplest design. Comparison studies between mild steel and aluminium alloys 6061 were made with a view to examine the most suitable material to be used. Based on the analysis, allowable maximum tolerance was set at 2.5µm and it was found that aluminium alloy 6061 suffice to be used.

  19. Vending machine assessment methodology. A systematic review.

    PubMed

    Matthews, Melissa A; Horacek, Tanya M

    2015-07-01

    The nutritional quality of food and beverage products sold in vending machines has been implicated as a contributing factor to the development of an obesogenic food environment. How comprehensive, reliable, and valid are the current assessment tools for vending machines to support or refute these claims? A systematic review was conducted to summarize, compare, and evaluate the current methodologies and available tools for vending machine assessment. A total of 24 relevant research studies published between 1981 and 2013 met inclusion criteria for this review. The methodological variables reviewed in this study include assessment tool type, study location, machine accessibility, product availability, healthfulness criteria, portion size, price, product promotion, and quality of scientific practice. There were wide variations in the depth of the assessment methodologies and product healthfulness criteria utilized among the reviewed studies. Of the reviewed studies, 39% evaluated machine accessibility, 91% evaluated product availability, 96% established healthfulness criteria, 70% evaluated portion size, 48% evaluated price, 52% evaluated product promotion, and 22% evaluated the quality of scientific practice. Of all reviewed articles, 87% reached conclusions that provided insight into the healthfulness of vended products and/or vending environment. Product healthfulness criteria and complexity for snack and beverage products was also found to be variable between the reviewed studies. These findings make it difficult to compare results between studies. A universal, valid, and reliable vending machine assessment tool that is comprehensive yet user-friendly is recommended. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Analysis towards VMEM File of a Suspended Virtual Machine

    NASA Astrophysics Data System (ADS)

    Song, Zheng; Jin, Bo; Sun, Yongqing

    With the popularity of virtual machines, forensic investigators are challenged with more complicated situations, among which discovering the evidences in virtualized environment is of significant importance. This paper mainly analyzes the file suffixed with .vmem in VMware Workstation, which stores all pseudo-physical memory into an image. The internal file structure of .vmem file is studied and disclosed. Key information about processes and threads of a suspended virtual machine is revealed. Further investigation into the Windows XP SP3 heap contents is conducted and a proof-of-concept tool is provided. Different methods to obtain forensic memory images are introduced, with both advantages and limits analyzed. We conclude with an outlook.

  1. Geometry and surface damage in micro electrical discharge machining of micro-holes

    NASA Astrophysics Data System (ADS)

    Ekmekci, Bülent; Sayar, Atakan; Tecelli Öpöz, Tahsin; Erden, Abdulkadir

    2009-10-01

    Geometry and subsurface damage of blind micro-holes produced by micro electrical discharge machining (micro-EDM) is investigated experimentally to explore the relational dependence with respect to pulse energy. For this purpose, micro-holes are machined with various pulse energies on plastic mold steel samples using a tungsten carbide tool electrode and a hydrocarbon-based dielectric liquid. Variations in the micro-hole geometry, micro-hole depth and over-cut in micro-hole diameter are measured. Then, unconventional etching agents are applied on the cross sections to examine micro structural alterations within the substrate. It is observed that the heat-damaged segment is composed of three distinctive layers, which have relatively high thicknesses and vary noticeably with respect to the drilling depth. Crack formation is identified on some sections of the micro-holes even by utilizing low pulse energies during machining. It is concluded that the cracking mechanism is different from cracks encountered on the surfaces when machining is performed by using the conventional EDM process. Moreover, an electrically conductive bridge between work material and debris particles is possible at the end tip during machining which leads to electric discharges between the piled segments of debris particles and the tool electrode during discharging.

  2. Agile Machining and Inspection Non-Nuclear Report (NNR) Project

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lazarus, Lloyd

    This report is a high level summary of the eight major projects funded by the Agile Machining and Inspection Non-Nuclear Readiness (NNR) project (FY06.0422.3.04.R1). The largest project of the group is the Rapid Response project in which the six major sub categories are summarized. This project focused on the operations of the machining departments that will comprise Special Applications Machining (SAM) in the Kansas City Responsive Infrastructure Manufacturing & Sourcing (KCRIMS) project. This project was aimed at upgrading older machine tools, developing new inspection tools, eliminating Classified Removable Electronic Media (CREM) in the handling of classified Numerical Control (NC) programsmore » by installing the CRONOS network, and developing methods to automatically load Coordinated-Measuring Machine (CMM) inspection data into bomb books and product score cards. Finally, the project personnel leaned perations of some of the machine tool cells, and now have the model to continue this activity.« less

  3. Method of Optimizing the Construction of Machining, Assembly and Control Devices

    NASA Astrophysics Data System (ADS)

    Iordache, D. M.; Costea, A.; Niţu, E. L.; Rizea, A. D.; Babă, A.

    2017-10-01

    Industry dynamics, driven by economic and social requirements, must generate more interest in technological optimization, capable of ensuring a steady development of advanced technical means to equip machining processes. For these reasons, the development of tools, devices, work equipment and control, as well as the modernization of machine tools, is the certain solution to modernize production systems that require considerable time and effort. This type of approach is also related to our theoretical, experimental and industrial applications of recent years, presented in this paper, which have as main objectives the elaboration and use of mathematical models, new calculation methods, optimization algorithms, new processing and control methods, as well as some structures for the construction and configuration of technological equipment with a high level of performance and substantially reduced costs..

  4. Machinability of IPS Empress 2 framework ceramic.

    PubMed

    Schmidt, C; Weigl, P

    2000-01-01

    Using ceramic materials for an automatic production of ceramic dentures by CAD/CAM is a challenge, because many technological, medical, and optical demands must be considered. The IPS Empress 2 framework ceramic meets most of them. This study shows the possibilities for machining this ceramic with economical parameters. The long life-time requirement for ceramic dentures requires a ductile machined surface to avoid the well-known subsurface damages of brittle materials caused by machining. Slow and rapid damage propagation begins at break outs and cracks, and limits life-time significantly. Therefore, ductile machined surfaces are an important demand for machine dental ceramics. The machining tests were performed with various parameters such as tool grain size and feed speed. Denture ceramics were machined by jig grinding on a 5-axis CNC milling machine (Maho HGF 500) with a high-speed spindle up to 120,000 rpm. The results of the wear test indicate low tool wear. With one tool, you can machine eight occlusal surfaces including roughing and finishing. One occlusal surface takes about 60 min machining time. Recommended parameters for roughing are middle diamond grain size (D107), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 1000 mm/min, depth of cut a(e) = 0.06 mm, width of contact a(p) = 0.8 mm, and for finishing ultra fine diamond grain size (D46), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 100 mm/min, depth of cut a(e) = 0.02 mm, width of contact a(p) = 0.8 mm. The results of the machining tests give a reference for using IPS Empress(R) 2 framework ceramic in CAD/CAM systems. Copyright 2000 John Wiley & Sons, Inc.

  5. A Boltzmann machine for the organization of intelligent machines

    NASA Technical Reports Server (NTRS)

    Moed, Michael C.; Saridis, George N.

    1989-01-01

    In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved

  6. Optical alignment of electrodes on electrical discharge machines

    NASA Technical Reports Server (NTRS)

    Boissevain, A. G.; Nelson, B. W.

    1972-01-01

    Shadowgraph system projects magnified image on screen so that alignment of small electrodes mounted on electrical discharge machines can be corrected and verified. Technique may be adapted to other machine tool equipment where physical contact cannot be made during inspection and access to tool limits conventional runout checking procedures.

  7. Deposition and micro electrical discharge machining of CVD-diamond layers incorporated with silicon

    NASA Astrophysics Data System (ADS)

    Kühn, R.; Berger, T.; Prieske, M.; Börner, R.; Hackert-Oschätzchen, M.; Zeidler, H.; Schubert, A.

    2017-10-01

    In metal forming, lubricants have to be used to prevent corrosion or to reduce friction and tool wear. From an economical and ecological point of view, the aim is to avoid the usage of lubricants. For dry deep drawing of aluminum sheets it is intended to apply locally micro-structured wear-resistant carbon based coatings onto steel tools. One type of these coatings are diamond layers prepared by chemical vapor deposition (CVD). Due to the high strength of diamond, milling processes are unsuitable for micro-structuring of these layers. In contrast to this, micro electrical discharge machining (micro EDM) is a suitable process for micro-structuring CVD-diamond layers. Due to its non-contact nature and its process principle of ablating material by melting and evaporating, it is independent of the hardness, brittleness or toughness of the workpiece material. In this study the deposition and micro electrical discharge machining of silicon incorporated CVD-diamond (Si-CVD-diamond) layers were presented. For this, 10 µm thick layers were deposited on molybdenum plates by a laser-induced plasma CVD process (LaPlas-CVD). For the characterization of the coatings RAMAN- and EDX-analyses were conducted. Experiments in EDM were carried out with a tungsten carbide tool electrode with a diameter of 90 µm to investigate the micro-structuring of Si-CVD-diamond. The impact of voltage, discharge energy and tool polarity on process speed and resulting erosion geometry were analyzed. The results show that micro EDM is a suitable technology for micro-structuring of silicon incorporated CVD-diamond layers.

  8. Highly Productive Tools For Turning And Milling

    NASA Astrophysics Data System (ADS)

    Vasilko, Karol

    2015-12-01

    Beside cutting speed, shift is another important parameter of machining. Its considerable influence is shown mainly in the workpiece machined surface microgeometry. In practice, mainly its combination with the radius of cutting tool tip rounding is used. Options to further increase machining productivity and machined surface quality are hidden in this approach. The paper presents variations of the design of productive cutting tools for lathe work and milling on the base of the use of the laws of the relationship among the highest reached uneveness of machined surface, tool tip radius and shift.

  9. A novel AFM-based 5-axis nanoscale machine tool for fabrication of nanostructures on a micro ball

    NASA Astrophysics Data System (ADS)

    Geng, Yanquan; Wang, Yuzhang; Yan, Yongda; Zhao, Xuesen

    2017-11-01

    This paper presents a novel atomic force microscopy (AFM)-based 5-axis nanoscale machine tool developed to fabricate nanostructures on different annuli of the micro ball. Different nanostructures can be obtained by combining the scratching trajectory of the AFM tip with the movement of the high precision air-bearing spindle. The center of the micro ball is aligned to be coincided with the gyration center of the high precision to guarantee the machining process during the rotating of the air-bearing spindle. Processing on different annuli of the micro ball is achieved by controlling the distance between the center of the micro ball and the rotation center of the AFM head. Nanostructures including square cavities, circular cavities, triangular cavities, and an annular nanochannel are machined successfully on the three different circumferences of a micro ball with a diameter of 1500 μm. Moreover, the influences of the error motions of the high precision air-bearing spindle and the eccentric between the micro ball and the gyration center of the high precision air-bearing spindle on the processing position error on the micro ball are also investigated. This proposed machining method has the potential to prepare the inertial confinement fusion target with the expected dimension defects, which would advance the application of the AFM tip-based nanomachining approach.

  10. Machine learning methods as a tool to analyse incomplete or irregularly sampled radon time series data.

    PubMed

    Janik, M; Bossew, P; Kurihara, O

    2018-07-15

    Machine learning is a class of statistical techniques which has proven to be a powerful tool for modelling the behaviour of complex systems, in which response quantities depend on assumed controls or predictors in a complicated way. In this paper, as our first purpose, we propose the application of machine learning to reconstruct incomplete or irregularly sampled data of time series indoor radon ( 222 Rn). The physical assumption underlying the modelling is that Rn concentration in the air is controlled by environmental variables such as air temperature and pressure. The algorithms "learn" from complete sections of multivariate series, derive a dependence model and apply it to sections where the controls are available, but not the response (Rn), and in this way complete the Rn series. Three machine learning techniques are applied in this study, namely random forest, its extension called the gradient boosting machine and deep learning. For a comparison, we apply the classical multiple regression in a generalized linear model version. Performance of the models is evaluated through different metrics. The performance of the gradient boosting machine is found to be superior to that of the other techniques. By applying learning machines, we show, as our second purpose, that missing data or periods of Rn series data can be reconstructed and resampled on a regular grid reasonably, if data of appropriate physical controls are available. The techniques also identify to which degree the assumed controls contribute to imputing missing Rn values. Our third purpose, though no less important from the viewpoint of physics, is identifying to which degree physical, in this case environmental variables, are relevant as Rn predictors, or in other words, which predictors explain most of the temporal variability of Rn. We show that variables which contribute most to the Rn series reconstruction, are temperature, relative humidity and day of the year. The first two are physical

  11. Design and application of a tool for structuring, capitalizing and making more accessible information and lessons learned from accidents involving machinery.

    PubMed

    Sadeghi, Samira; Sadeghi, Leyla; Tricot, Nicolas; Mathieu, Luc

    2017-12-01

    Accident reports are published in order to communicate the information and lessons learned from accidents. An efficient accident recording and analysis system is a necessary step towards improvement of safety. However, currently there is a shortage of efficient tools to support such recording and analysis. In this study we introduce a flexible and customizable tool that allows structuring and analysis of this information. This tool has been implemented under TEEXMA®. We named our prototype TEEXMA®SAFETY. This tool provides an information management system to facilitate data collection, organization, query, analysis and reporting of accidents. A predefined information retrieval module provides ready access to data which allows the user to quickly identify the possible hazards for specific machines and provides information on the source of hazards. The main target audience for this tool includes safety personnel, accident reporters and designers. The proposed data model has been developed by analyzing different accident reports.

  12. Tribology in secondary wood machining

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ko, P.L.; Hawthorne, H.M.; Andiappan, J.

    Secondary wood manufacturing covers a wide range of products from furniture, cabinets, doors and windows, to musical instruments. Many of these are now mass produced in sophisticated, high speed numerical controlled machines. The performance and the reliability of the tools are key to an efficient and economical manufacturing process as well as to the quality of the finished products. A program concerned with three aspects of tribology of wood machining, namely, tool wear, tool-wood friction characteristics and wood surface quality characterization, was set up in the Integrated Manufacturing Technologies Institute (IMTI) of the National Research Council of Canada. The studiesmore » include friction and wear mechanism identification and modeling, wear performance of surface-engineered tool materials, friction-induced vibration and cutting efficiency, and the influence of wear and friction on finished products. This research program underlines the importance of tribology in secondary wood manufacturing and at the same time adds new challenges to tribology research since wood is a complex, heterogeneous, material and its behavior during machining is highly sensitive to the surrounding environments and to the moisture content in the work piece.« less

  13. Machining of Fibre Reinforced Plastic Composite Materials.

    PubMed

    Caggiano, Alessandra

    2018-03-18

    Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented.

  14. Machining of Fibre Reinforced Plastic Composite Materials

    PubMed Central

    2018-01-01

    Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented. PMID:29562635

  15. A Practical Framework Toward Prediction of Breaking Force and Disintegration of Tablet Formulations Using Machine Learning Tools.

    PubMed

    Akseli, Ilgaz; Xie, Jingjin; Schultz, Leon; Ladyzhynsky, Nadia; Bramante, Tommasina; He, Xiaorong; Deanne, Rich; Horspool, Keith R; Schwabe, Robert

    2017-01-01

    Enabling the paradigm of quality by design requires the ability to quantitatively correlate material properties and process variables to measureable product performance attributes. Conventional, quality-by-test methods for determining tablet breaking force and disintegration time usually involve destructive tests, which consume significant amount of time and labor and provide limited information. Recent advances in material characterization, statistical analysis, and machine learning have provided multiple tools that have the potential to develop nondestructive, fast, and accurate approaches in drug product development. In this work, a methodology to predict the breaking force and disintegration time of tablet formulations using nondestructive ultrasonics and machine learning tools was developed. The input variables to the model include intrinsic properties of formulation and extrinsic process variables influencing the tablet during manufacturing. The model has been applied to predict breaking force and disintegration time using small quantities of active pharmaceutical ingredient and prototype formulation designs. The novel approach presented is a step forward toward rational design of a robust drug product based on insight into the performance of common materials during formulation and process development. It may also help expedite drug product development timeline and reduce active pharmaceutical ingredient usage while improving efficiency of the overall process. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  16. Automatic Tool for Local Assembly Structures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Whole community shotgun sequencing of total DNA (i.e. metagenomics) and total RNA (i.e. metatranscriptomics) has provided a wealth of information in the microbial community structure, predicted functions, metabolic networks, and is even able to reconstruct complete genomes directly. Here we present ATLAS (Automatic Tool for Local Assembly Structures) a comprehensive pipeline for assembly, annotation, genomic binning of metagenomic and metatranscriptomic data with an integrated framework for Multi-Omics. This will provide an open source tool for the Multi-Omic community at large.

  17. Machine learning for neuroimaging with scikit-learn.

    PubMed

    Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

    2014-01-01

    Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

  18. Machine learning for neuroimaging with scikit-learn

    PubMed Central

    Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

    2014-01-01

    Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388

  19. Structure prediction of boron-doped graphene by machine learning

    NASA Astrophysics Data System (ADS)

    M. Dieb, Thaer; Hou, Zhufeng; Tsuda, Koji

    2018-06-01

    Heteroatom doping has endowed graphene with manifold aspects of material properties and boosted its applications. The atomic structure determination of doped graphene is vital to understand its material properties. Motivated by the recently synthesized boron-doped graphene with relatively high concentration, here we employ machine learning methods to search the most stable structures of doped boron atoms in graphene, in conjunction with the atomistic simulations. From the determined stable structures, we find that in the free-standing pristine graphene, the doped boron atoms energetically prefer to substitute for the carbon atoms at different sublattice sites and that the para configuration of boron-boron pair is dominant in the cases of high boron concentrations. The boron doping can increase the work function of graphene by 0.7 eV for a boron content higher than 3.1%.

  20. Wear resistance of machine tools' bionic linear rolling guides by laser cladding

    NASA Astrophysics Data System (ADS)

    Wang, Yiqiang; Liu, Botao; Guo, Zhengcai

    2017-06-01

    In order to improve the rolling wear resistance (RWR) of linear rolling guides (LRG) as well as prolong the life of machine tools, various shape samples with different units spaces ranged from 1 to 5 mm are designed through the observation of animals in the desert and manufactured by laser cladding. Wear resistance tests reproducing closely the real operational condition are conducted by using a homemade linear reciprocating wear test machine, and wear resistance is evaluated by means of weight loss measurement. Results indicate that the samples with bionic units have better RWR than the untreated one, of which the reticulate treated sample with unit space 3 mm present the best RWR. More specifically, among the punctuate treated samples, the mass loss increases with the increase of unit space; among the striate treated samples, the mass loss changes slightly with the increase of unit space, attaining a minimum at the unit space of 4 mm; among the reticulate treated samples, with the increase of unit space, the mass loss initially decreases, but turns to increase after reaching a minimum at the unit space of 3 mm. Additionally, the samples with striate shape perform better wear resistance than the other shape groups on the whole. From the ratio value of laser treated area to contacted area perspective, that the samples with ratio value between 0.15 and 0.3 possess better wear resistance is concluded.

  1. Effect of Built-Up Edge Formation during Stable State of Wear in AISI 304 Stainless Steel on Machining Performance and Surface Integrity of the Machined Part.

    PubMed

    Ahmed, Yassmin Seid; Fox-Rabinovich, German; Paiva, Jose Mario; Wagg, Terry; Veldhuis, Stephen Clarence

    2017-10-25

    During machining of stainless steels at low cutting -speeds, workpiece material tends to adhere to the cutting tool at the tool-chip interface, forming built-up edge (BUE). BUE has a great importance in machining processes; it can significantly modify the phenomenon in the cutting zone, directly affecting the workpiece surface integrity, cutting tool forces, and chip formation. The American Iron and Steel Institute (AISI) 304 stainless steel has a high tendency to form an unstable BUE, leading to deterioration of the surface quality. Therefore, it is necessary to understand the nature of the surface integrity induced during machining operations. Although many reports have been published on the effect of tool wear during machining of AISI 304 stainless steel on surface integrity, studies on the influence of the BUE phenomenon in the stable state of wear have not been investigated so far. The main goal of the present work is to investigate the close link between the BUE formation, surface integrity and cutting forces in the stable sate of wear for uncoated cutting tool during the cutting tests of AISI 304 stainless steel. The cutting parameters were chosen to induce BUE formation during machining. X-ray diffraction (XRD) method was used for measuring superficial residual stresses of the machined surface through the stable state of wear in the cutting and feed directions. In addition, surface roughness of the machined surface was investigated using the Alicona microscope and Scanning Electron Microscopy (SEM) was used to reveal the surface distortions created during the cutting process, combined with chip undersurface analyses. The investigated BUE formation during the stable state of wear showed that the BUE can cause a significant improvement in the surface integrity and cutting forces. Moreover, it can be used to compensate for tool wear through changing the tool geometry, leading to the protection of the cutting tool from wear.

  2. Light-operated machines based on threaded molecular structures.

    PubMed

    Credi, Alberto; Silvi, Serena; Venturi, Margherita

    2014-01-01

    Rotaxanes and related species represent the most common implementation of the concept of artificial molecular machines, because the supramolecular nature of the interactions between the components and their interlocked architecture allow a precise control on the position and movement of the molecular units. The use of light to power artificial molecular machines is particularly valuable because it can play the dual role of "writing" and "reading" the system. Moreover, light-driven machines can operate without accumulation of waste products, and photons are the ideal inputs to enable autonomous operation mechanisms. In appropriately designed molecular machines, light can be used to control not only the stability of the system, which affects the relative position of the molecular components but also the kinetics of the mechanical processes, thereby enabling control on the direction of the movements. This step forward is necessary in order to make a leap from molecular machines to molecular motors.

  3. Heat-Assisted Machining for Material Removal Improvement

    NASA Astrophysics Data System (ADS)

    Mohd Hadzley, A. B.; Hafiz, S. Muhammad; Azahar, W.; Izamshah, R.; Mohd Shahir, K.; Abu, A.

    2015-09-01

    Heat assisted machining (HAM) is a process where an intense heat source is used to locally soften the workpiece material before machined by high speed cutting tool. In this paper, an HAM machine is developed by modification of small CNC machine with the addition of special jig to hold the heat sources in front of the machine spindle. Preliminary experiment to evaluate the capability of HAM machine to produce groove formation for slotting process was conducted. A block AISI D2 tool steel with100mm (width) × 100mm (length) × 20mm (height) size has been cut by plasma heating with different setting of arc current, feed rate and air pressure. Their effect has been analyzed based on distance of cut (DOC).Experimental results demonstrated the most significant factor that contributed to the DOC is arc current, followed by the feed rate and air pressure. HAM improves the slotting process of AISI D2 by increasing distance of cut due to initial cutting groove that formed during thermal melting and pressurized air from the heat source.

  4. Structural Elements Regulating AAA+ Protein Quality Control Machines.

    PubMed

    Chang, Chiung-Wen; Lee, Sukyeong; Tsai, Francis T F

    2017-01-01

    Members of the ATPases Associated with various cellular Activities (AAA+) superfamily participate in essential and diverse cellular pathways in all kingdoms of life by harnessing the energy of ATP binding and hydrolysis to drive their biological functions. Although most AAA+ proteins share a ring-shaped architecture, AAA+ proteins have evolved distinct structural elements that are fine-tuned to their specific functions. A central question in the field is how ATP binding and hydrolysis are coupled to substrate translocation through the central channel of ring-forming AAA+ proteins. In this mini-review, we will discuss structural elements present in AAA+ proteins involved in protein quality control, drawing similarities to their known role in substrate interaction by AAA+ proteins involved in DNA translocation. Elements to be discussed include the pore loop-1, the Inter-Subunit Signaling (ISS) motif, and the Pre-Sensor I insert (PS-I) motif. Lastly, we will summarize our current understanding on the inter-relationship of those structural elements and propose a model how ATP binding and hydrolysis might be coupled to polypeptide translocation in protein quality control machines.

  5. “Investigations on the machinability of Waspaloy under dry environment”

    NASA Astrophysics Data System (ADS)

    Deepu, J.; Kuppan, P.; SBalan, A. S.; Oyyaravelu, R.

    2016-09-01

    Nickel based superalloy, Waspaloy is extensively used in gas turbine, aerospace and automobile industries because of their unique combination of properties like high strength at elevated temperatures, resistance to chemical degradation and excellent wear resistance in many hostile environments. It is considered as one of the difficult to machine superalloy due to excessive tool wear and poor surface finish. The present paper is an attempt for removing cutting fluids from turning process of Waspaloy and to make the processes environmentally safe. For this purpose, the effect of machining parameters such as cutting speed and feed rate on the cutting force, cutting temperature, surface finish and tool wear were investigated barrier. Consequently, the strength and tool wear resistance and tool life increased significantly. Response Surface Methodology (RSM) has been used for developing and analyzing a mathematical model which describes the relationship between machining parameters and output variables. Subsequently ANOVA was used to check the adequacy of the regression model as well as each machining variables. The optimal cutting parameters were determined based on multi-response optimizations by composite desirability approach in order to minimize cutting force, average surface roughness and maximum flank wear. The results obtained from the experiments shown that machining of Waspaloy using coated carbide tool with special ranges of parameters, cutting fluid could be completely removed from machining process

  6. Optimization of Cvd Diamond Coating Type on Micro Drills in Pcb Machining

    NASA Astrophysics Data System (ADS)

    Lei, X. L.; He, Y.; Sun, F. H.

    2016-12-01

    The demand for better tools for machining printed circuit boards (PCBs) is increasing due to the extensive usage of these boards in digital electronic products. This paper is aimed at optimizing coating type on micro drills in order to extend their lifetime in PCB machining. First, the tribotests involving micro crystalline diamond (MCD), nano crystalline diamond (NCD) and bare tungsten carbide (WC-Co) against PCBs show that NCD-PCB tribopair exhibits the lowest friction coefficient (0.35) due to the unique nano structure and low surface roughness of NCD films. Thereafter, the dry machining performance of the MCD- and NCD-coated micro drills on PCBs is systematically studied, using diamond-like coating (DLC) and TiAlN-coated micro drills as comparison. The experiments show that the working lives of these micro drills can be ranked as: NCD>TiAlN>DLC>MCD>bare WC-Co. The superior cutting performance of NCD-coated micro drills in terms of the lowest flank wear growth rate, no tool degradation (e.g. chipping, tool tipping) appearance, the best hole quality as well as the lowest feed force may come from the excellent wear resistance, lower friction coefficient against PCB as well as the high adhesive strength on the underneath substrate of NCD films.

  7. GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies

    PubMed Central

    Zhang, Bing; Schmoyer, Denise; Kirov, Stefan; Snoddy, Jay

    2004-01-01

    Background Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets. Results We have created a web-based tool for data analysis and data visualization for sets of genes called GOTree Machine (GOTM). This tool was originally intended to analyze sets of co-regulated genes identified from microarray analysis but is adaptable for use with other gene sets from other high-throughput analyses. GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets. This system provides user friendly data navigation and visualization. Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study. GOTree Machine is available online at . Conclusion GOTree Machine has a broad application in functional genomic, proteomic and other high-throughput methods that generate large sets of interesting genes; its primary purpose is to help users sort for interesting patterns in gene sets. PMID:14975175

  8. The white matter structural network underlying human tool use and tool understanding.

    PubMed

    Bi, Yanchao; Han, Zaizhu; Zhong, Suyu; Ma, Yujun; Gong, Gaolang; Huang, Ruiwang; Song, Luping; Fang, Yuxing; He, Yong; Caramazza, Alfonso

    2015-04-29

    The ability to recognize, create, and use complex tools is a milestone in human evolution. Widely distributed brain regions in parietal, frontal, and temporal cortices have been implicated in using and understanding tools, but the roles of their anatomical connections in supporting tool use and tool conceptual behaviors are unclear. Using deterministic fiber tracking in healthy participants, we first examined how 14 cortical regions that are consistently activated by tool processing are connected by white matter (WM) tracts. The relationship between the integrity of each of the 33 obtained tracts and tool processing deficits across 86 brain-damaged patients was investigated. WM tract integrity was measured with both lesion percentage (structural imaging) and mean fractional anisotropy (FA) values (diffusion imaging). Behavioral abilities were assessed by a tool use task, a range of conceptual tasks, and control tasks. We found that three left hemisphere tracts connecting frontoparietal and intrafrontal areas overlapping with left superior longitudinal fasciculus are crucial for tool use such that larger lesion and lower mean FA values on these tracts were associated with more severe tool use deficits. These tracts and five additional left hemisphere tracts connecting frontal and temporal/parietal regions, mainly overlapping with left superior longitudinal fasciculus, inferior frontooccipital fasciculus, uncinate fasciculus, and anterior thalamic radiation, are crucial for tool concept processing. Largely consistent results were also obtained using voxel-based symptom mapping analyses. Our results revealed the WM structural networks that support the use and conceptual understanding of tools, providing evidence for the anatomical skeleton of the tool knowledge network. Copyright © 2015 the authors 0270-6474/15/356822-14$15.00/0.

  9. Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

    NASA Astrophysics Data System (ADS)

    Kant Garg, Girish; Garg, Suman; Sangwan, K. S.

    2018-04-01

    The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.

  10. Characteristics for electrochemical machining with nanoscale voltage pulses.

    PubMed

    Lee, E S; Back, S Y; Lee, J T

    2009-06-01

    Electrochemical machining has traditionally been used in highly specialized fields, such as those of the aerospace and defense industries. It is now increasingly being applied in other industries, where parts with difficult-to-cut material, complex geometry and tribology, and devices of nanoscale and microscale are required. Electric characteristic plays a principal function role in and chemical characteristic plays an assistant function role in electrochemical machining. Therefore, essential parameters in electrochemical machining can be described current density, machining time, inter-electrode gap size, electrolyte, electrode shape etc. Electrochemical machining provides an economical and effective method for machining high strength, high tension and heat-resistant materials into complex shapes such as turbine blades of titanium and aluminum alloys. The application of nanoscale voltage pulses between a tool electrode and a workpiece in an electrochemical environment allows the three-dimensional machining of conducting materials with sub-micrometer precision. In this study, micro probe are developed by electrochemical etching and micro holes are manufactured using these micro probe as tool electrodes. Micro holes and microgroove can be accurately achieved by using nanoscale voltages pulses.

  11. Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm.

    PubMed

    Pizarro, Ricardo A; Cheng, Xi; Barnett, Alan; Lemaitre, Herve; Verchinski, Beth A; Goldman, Aaron L; Xiao, Ena; Luo, Qian; Berman, Karen F; Callicott, Joseph H; Weinberger, Daniel R; Mattay, Venkata S

    2016-01-01

    High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

  12. Influence of Electrical Resistivity and Machining Parameters on Electrical Discharge Machining Performance of Engineering Ceramics

    PubMed Central

    Ji, Renjie; Liu, Yonghong; Diao, Ruiqiang; Xu, Chenchen; Li, Xiaopeng; Cai, Baoping; Zhang, Yanzhen

    2014-01-01

    Engineering ceramics have been widely used in modern industry for their excellent physical and mechanical properties, and they are difficult to machine owing to their high hardness and brittleness. Electrical discharge machining (EDM) is the appropriate process for machining engineering ceramics provided they are electrically conducting. However, the electrical resistivity of the popular engineering ceramics is higher, and there has been no research on the relationship between the EDM parameters and the electrical resistivity of the engineering ceramics. This paper investigates the effects of the electrical resistivity and EDM parameters such as tool polarity, pulse interval, and electrode material, on the ZnO/Al2O3 ceramic's EDM performance, in terms of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The results show that the electrical resistivity and the EDM parameters have the great influence on the EDM performance. The ZnO/Al2O3 ceramic with the electrical resistivity up to 3410 Ω·cm can be effectively machined by EDM with the copper electrode, the negative tool polarity, and the shorter pulse interval. Under most machining conditions, the MRR increases, and the SR decreases with the decrease of electrical resistivity. Moreover, the tool polarity, and pulse interval affect the EWR, respectively, and the electrical resistivity and electrode material have a combined effect on the EWR. Furthermore, the EDM performance of ZnO/Al2O3 ceramic with the electrical resistivity higher than 687 Ω·cm is obviously different from that with the electrical resistivity lower than 687 Ω·cm, when the electrode material changes. The microstructure character analysis of the machined ZnO/Al2O3 ceramic surface shows that the ZnO/Al2O3 ceramic is removed by melting, evaporation and thermal spalling, and the material from the working fluid and the graphite electrode can transfer to the workpiece surface during electrical discharge

  13. Influence of electrical resistivity and machining parameters on electrical discharge machining performance of engineering ceramics.

    PubMed

    Ji, Renjie; Liu, Yonghong; Diao, Ruiqiang; Xu, Chenchen; Li, Xiaopeng; Cai, Baoping; Zhang, Yanzhen

    2014-01-01

    Engineering ceramics have been widely used in modern industry for their excellent physical and mechanical properties, and they are difficult to machine owing to their high hardness and brittleness. Electrical discharge machining (EDM) is the appropriate process for machining engineering ceramics provided they are electrically conducting. However, the electrical resistivity of the popular engineering ceramics is higher, and there has been no research on the relationship between the EDM parameters and the electrical resistivity of the engineering ceramics. This paper investigates the effects of the electrical resistivity and EDM parameters such as tool polarity, pulse interval, and electrode material, on the ZnO/Al2O3 ceramic's EDM performance, in terms of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The results show that the electrical resistivity and the EDM parameters have the great influence on the EDM performance. The ZnO/Al2O3 ceramic with the electrical resistivity up to 3410 Ω·cm can be effectively machined by EDM with the copper electrode, the negative tool polarity, and the shorter pulse interval. Under most machining conditions, the MRR increases, and the SR decreases with the decrease of electrical resistivity. Moreover, the tool polarity, and pulse interval affect the EWR, respectively, and the electrical resistivity and electrode material have a combined effect on the EWR. Furthermore, the EDM performance of ZnO/Al2O3 ceramic with the electrical resistivity higher than 687 Ω·cm is obviously different from that with the electrical resistivity lower than 687 Ω·cm, when the electrode material changes. The microstructure character analysis of the machined ZnO/Al2O3 ceramic surface shows that the ZnO/Al2O3 ceramic is removed by melting, evaporation and thermal spalling, and the material from the working fluid and the graphite electrode can transfer to the workpiece surface during electrical discharge

  14. Effect of Built-Up Edge Formation during Stable State of Wear in AISI 304 Stainless Steel on Machining Performance and Surface Integrity of the Machined Part

    PubMed Central

    Fox-Rabinovich, German; Wagg, Terry

    2017-01-01

    During machining of stainless steels at low cutting -speeds, workpiece material tends to adhere to the cutting tool at the tool–chip interface, forming built-up edge (BUE). BUE has a great importance in machining processes; it can significantly modify the phenomenon in the cutting zone, directly affecting the workpiece surface integrity, cutting tool forces, and chip formation. The American Iron and Steel Institute (AISI) 304 stainless steel has a high tendency to form an unstable BUE, leading to deterioration of the surface quality. Therefore, it is necessary to understand the nature of the surface integrity induced during machining operations. Although many reports have been published on the effect of tool wear during machining of AISI 304 stainless steel on surface integrity, studies on the influence of the BUE phenomenon in the stable state of wear have not been investigated so far. The main goal of the present work is to investigate the close link between the BUE formation, surface integrity and cutting forces in the stable sate of wear for uncoated cutting tool during the cutting tests of AISI 304 stainless steel. The cutting parameters were chosen to induce BUE formation during machining. X-ray diffraction (XRD) method was used for measuring superficial residual stresses of the machined surface through the stable state of wear in the cutting and feed directions. In addition, surface roughness of the machined surface was investigated using the Alicona microscope and Scanning Electron Microscopy (SEM) was used to reveal the surface distortions created during the cutting process, combined with chip undersurface analyses. The investigated BUE formation during the stable state of wear showed that the BUE can cause a significant improvement in the surface integrity and cutting forces. Moreover, it can be used to compensate for tool wear through changing the tool geometry, leading to the protection of the cutting tool from wear. PMID:29068405

  15. Investigations on high speed machining of EN-353 steel alloy under different machining environments

    NASA Astrophysics Data System (ADS)

    Venkata Vishnu, A.; Jamaleswara Kumar, P.

    2018-03-01

    The addition of Nano Particles into conventional cutting fluids enhances its cooling capabilities; in the present paper an attempt is made by adding nano sized particles into conventional cutting fluids. Taguchi Robust Design Methodology is employed in order to study the performance characteristics of different turning parameters i.e. cutting speed, feed rate, depth of cut and type of tool under different machining environments i.e. dry machining, machining with lubricant - SAE 40 and machining with mixture of nano sized particles of Boric acid and base fluid SAE 40. A series of turning operations were performed using L27 (3)13 orthogonal array, considering high cutting speeds and the other machining parameters to measure hardness. The results are compared among the different machining environments, and it is concluded that there is considerable improvement in the machining performance using lubricant SAE 40 and mixture of SAE 40 + boric acid compared with dry machining. The ANOVA suggests that the selected parameters and the interactions are significant and cutting speed has most significant effect on hardness.

  16. Electrochemical micro/nano-machining: principles and practices.

    PubMed

    Zhan, Dongping; Han, Lianhuan; Zhang, Jie; He, Quanfeng; Tian, Zhao-Wu; Tian, Zhong-Qun

    2017-03-06

    Micro/nano-machining (MNM) is becoming the cutting-edge of high-tech manufacturing because of the increasing industrial demand for supersmooth surfaces and functional three-dimensional micro/nano-structures (3D-MNS) in ultra-large scale integrated circuits, microelectromechanical systems, miniaturized total analysis systems, precision optics, and so on. Taking advantage of no tool wear, no surface stress, environmental friendliness, simple operation, and low cost, electrochemical micro/nano-machining (EC-MNM) has an irreplaceable role in MNM. This comprehensive review presents the state-of-art of EC-MNM techniques for direct writing, surface planarization and polishing, and 3D-MNS fabrications. The key point of EC-MNM is to confine electrochemical reactions at the micro/nano-meter scale. This review will bring together various solutions to "confined reaction" ranging from electrochemical principles through technical characteristics to relevant applications.

  17. MOD Tool (Microwave Optics Design Tool)

    NASA Technical Reports Server (NTRS)

    Katz, Daniel S.; Borgioli, Andrea; Cwik, Tom; Fu, Chuigang; Imbriale, William A.; Jamnejad, Vahraz; Springer, Paul L.

    1999-01-01

    The Jet Propulsion Laboratory (JPL) is currently designing and building a number of instruments that operate in the microwave and millimeter-wave bands. These include MIRO (Microwave Instrument for the Rosetta Orbiter), MLS (Microwave Limb Sounder), and IMAS (Integrated Multispectral Atmospheric Sounder). These instruments must be designed and built to meet key design criteria (e.g., beamwidth, gain, pointing) obtained from the scientific goals for the instrument. These criteria are frequently functions of the operating environment (both thermal and mechanical). To design and build instruments which meet these criteria, it is essential to be able to model the instrument in its environments. Currently, a number of modeling tools exist. Commonly used tools at JPL include: FEMAP (meshing), NASTRAN (structural modeling), TRASYS and SINDA (thermal modeling), MACOS/IMOS (optical modeling), and POPO (physical optics modeling). Each of these tools is used by an analyst, who models the instrument in one discipline. The analyst then provides the results of this modeling to another analyst, who continues the overall modeling in another discipline. There is a large reengineering task in place at JPL to automate and speed-up the structural and thermal modeling disciplines, which does not include MOD Tool. The focus of MOD Tool (and of this paper) is in the fields unique to microwave and millimeter-wave instrument design. These include initial design and analysis of the instrument without thermal or structural loads, the automation of the transfer of this design to a high-end CAD tool, and the analysis of the structurally deformed instrument (due to structural and/or thermal loads). MOD Tool is a distributed tool, with a database of design information residing on a server, physical optics analysis being performed on a variety of supercomputer platforms, and a graphical user interface (GUI) residing on the user's desktop computer. The MOD Tool client is being developed using Tcl

  18. Micro-optical fabrication by ultraprecision diamond machining and precision molding

    NASA Astrophysics Data System (ADS)

    Li, Hui; Li, Likai; Naples, Neil J.; Roblee, Jeffrey W.; Yi, Allen Y.

    2017-06-01

    Ultraprecision diamond machining and high volume molding for affordable high precision high performance optical elements are becoming a viable process in optical industry for low cost high quality microoptical component manufacturing. In this process, first high precision microoptical molds are fabricated using ultraprecision single point diamond machining followed by high volume production methods such as compression or injection molding. In the last two decades, there have been steady improvements in ultraprecision machine design and performance, particularly with the introduction of both slow tool and fast tool servo. Today optical molds, including freeform surfaces and microlens arrays, are routinely diamond machined to final finish without post machining polishing. For consumers, compression molding or injection molding provide efficient and high quality optics at extremely low cost. In this paper, first ultraprecision machine design and machining processes such as slow tool and fast too servo are described then both compression molding and injection molding of polymer optics are discussed. To implement precision optical manufacturing by molding, numerical modeling can be included in the future as a critical part of the manufacturing process to ensure high product quality.

  19. Stochastic Simulation Tool for Aerospace Structural Analysis

    NASA Technical Reports Server (NTRS)

    Knight, Norman F.; Moore, David F.

    2006-01-01

    Stochastic simulation refers to incorporating the effects of design tolerances and uncertainties into the design analysis model and then determining their influence on the design. A high-level evaluation of one such stochastic simulation tool, the MSC.Robust Design tool by MSC.Software Corporation, has been conducted. This stochastic simulation tool provides structural analysts with a tool to interrogate their structural design based on their mathematical description of the design problem using finite element analysis methods. This tool leverages the analyst's prior investment in finite element model development of a particular design. The original finite element model is treated as the baseline structural analysis model for the stochastic simulations that are to be performed. A Monte Carlo approach is used by MSC.Robust Design to determine the effects of scatter in design input variables on response output parameters. The tool was not designed to provide a probabilistic assessment, but to assist engineers in understanding cause and effect. It is driven by a graphical-user interface and retains the engineer-in-the-loop strategy for design evaluation and improvement. The application problem for the evaluation is chosen to be a two-dimensional shell finite element model of a Space Shuttle wing leading-edge panel under re-entry aerodynamic loading. MSC.Robust Design adds value to the analysis effort by rapidly being able to identify design input variables whose variability causes the most influence in response output parameters.

  20. MISR Center Block Time Tool

    Atmospheric Science Data Center

    2013-04-01

      MISR Center Block Time Tool The misr_time tool calculates the block center times for MISR Level 1B2 files. This is ... version of the IDL package or by using the IDL Virtual Machine application. The IDL Virtual Machine is bundled with IDL and is ...

  1. Machine learning-based assessment tool for imbalance and vestibular dysfunction with virtual reality rehabilitation system.

    PubMed

    Yeh, Shih-Ching; Huang, Ming-Chun; Wang, Pa-Chun; Fang, Te-Yung; Su, Mu-Chun; Tsai, Po-Yi; Rizzo, Albert

    2014-10-01

    Dizziness is a major consequence of imbalance and vestibular dysfunction. Compared to surgery and drug treatments, balance training is non-invasive and more desired. However, training exercises are usually tedious and the assessment tool is insufficient to diagnose patient's severity rapidly. An interactive virtual reality (VR) game-based rehabilitation program that adopted Cawthorne-Cooksey exercises, and a sensor-based measuring system were introduced. To verify the therapeutic effect, a clinical experiment with 48 patients and 36 normal subjects was conducted. Quantified balance indices were measured and analyzed by statistical tools and a Support Vector Machine (SVM) classifier. In terms of balance indices, patients who completed the training process are progressed and the difference between normal subjects and patients is obvious. Further analysis by SVM classifier show that the accuracy of recognizing the differences between patients and normal subject is feasible, and these results can be used to evaluate patients' severity and make rapid assessment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  2. Machine learning and data science in soft materials engineering

    NASA Astrophysics Data System (ADS)

    Ferguson, Andrew L.

    2018-01-01

    In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by ‘de-jargonizing’ data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

  3. Machine learning and data science in soft materials engineering.

    PubMed

    Ferguson, Andrew L

    2018-01-31

    In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by 'de-jargonizing' data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

  4. The Machine Scoring of Writing

    ERIC Educational Resources Information Center

    McCurry, Doug

    2010-01-01

    This article provides an introduction to the kind of computer software that is used to score student writing in some high stakes testing programs, and that is being promoted as a teaching and learning tool to schools. It sketches the state of play with machines for the scoring of writing, and describes how these machines work and what they do.…

  5. Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

    PubMed

    Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

    2017-09-21

    Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

  6. Three-dimensional tool radius compensation for multi-axis peripheral milling

    NASA Astrophysics Data System (ADS)

    Chen, Youdong; Wang, Tianmiao

    2013-05-01

    Few function about 3D tool radius compensation is applied to generating executable motion control commands in the existing computer numerical control (CNC) systems. Once the tool radius is changed, especially in the case of tool size changing with tool wear in machining, a new NC program has to be recreated. A generic 3D tool radius compensation method for multi-axis peripheral milling in CNC systems is presented. The offset path is calculated by offsetting the tool path along the direction of the offset vector with a given distance. The offset vector is perpendicular to both the tangent vector of the tool path and the orientation vector of the tool axis relative to the workpiece. The orientation vector equations of the tool axis relative to the workpiece are obtained through homogeneous coordinate transformation matrix and forward kinematics of generalized kinematics model of multi-axis machine tools. To avoid cutting into the corner formed by the two adjacent tool paths, the coordinates of offset path at the intersection point have been calculated according to the transition type that is determined by the angle between the two tool path tangent vectors at the corner. Through the verification by the solid cutting simulation software VERICUT® with different tool radiuses on a table-tilting type five-axis machine tool, and by the real machining experiment of machining a soup spoon on a five-axis machine tool with the developed CNC system, the effectiveness of the proposed 3D tool radius compensation method is confirmed. The proposed compensation method can be suitable for all kinds of three- to five-axis machine tools as a general form.

  7. Comparative study of coated and uncoated tool inserts with dry machining of EN47 steel using Taguchi L9 optimization technique

    NASA Astrophysics Data System (ADS)

    Vasu, M.; Shivananda, Nayaka H.

    2018-04-01

    EN47 steel samples are machined on a self-centered lathe using Chemical Vapor Deposition of coated TiCN/Al2O3/TiN and uncoated tungsten carbide tool inserts, with nose radius 0.8mm. Results are compared with each other and optimized using statistical tool. Input (cutting) parameters that are considered in this work are feed rate (f), cutting speed (Vc), and depth of cut (ap), the optimization criteria are based on the Taguchi (L9) orthogonal array. ANOVA method is adopted to evaluate the statistical significance and also percentage contribution for each model. Multiple response characteristics namely cutting force (Fz), tool tip temperature (T) and surface roughness (Ra) are evaluated. The results discovered that coated tool insert (TiCN/Al2O3/TiN) exhibits 1.27 and 1.29 times better than the uncoated tool insert for tool tip temperature and surface roughness respectively. A slight increase in cutting force was observed for coated tools.

  8. Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods

    NASA Astrophysics Data System (ADS)

    Cubuk, E. D.; Schoenholz, S. S.; Rieser, J. M.; Malone, B. D.; Rottler, J.; Durian, D. J.; Kaxiras, E.; Liu, A. J.

    2015-03-01

    We use machine-learning methods on local structure to identify flow defects—or particles susceptible to rearrangement—in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.

  9. Computer-Aided Drafting and Design Series. Educational Resources for the Machine Tool Industry, Course Syllabi, [and] Instructor's Handbook. Student Laboratory Manual.

    ERIC Educational Resources Information Center

    Texas State Technical Coll. System, Waco.

    This package consists of course syllabi, an instructor's handbook, and a student laboratory manual for a 2-year vocational training program to prepare students for entry-level employment in computer-aided drafting and design in the machine tool industry. The program was developed through a modification of the DACUM (Developing a Curriculum)…

  10. Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

    PubMed

    Li, Yang; Yang, Jianyi

    2017-04-24

    The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

  11. Multicutter machining of compound parametric surfaces

    NASA Astrophysics Data System (ADS)

    Hatna, Abdelmadjid; Grieve, R. J.; Broomhead, P.

    2000-10-01

    Parametric free forms are used in industries as disparate as footwear, toys, sporting goods, ceramics, digital content creation, and conceptual design. Optimizing tool path patterns and minimizing the total machining time is a primordial issue in numerically controlled (NC) machining of free form surfaces. We demonstrate in the present work that multi-cutter machining can achieve as much as 60% reduction in total machining time for compound sculptured surfaces. The given approach is based upon the pre-processing as opposed to the usual post-processing of surfaces for the detection and removal of interference followed by precise tracking of unmachined areas.

  12. An FMS Dynamic Production Scheduling Algorithm Considering Cutting Tool Failure and Cutting Tool Life

    NASA Astrophysics Data System (ADS)

    Setiawan, A.; Wangsaputra, R.; Martawirya, Y. Y.; Halim, A. H.

    2016-02-01

    This paper deals with Flexible Manufacturing System (FMS) production rescheduling due to unavailability of cutting tools caused either of cutting tool failure or life time limit. The FMS consists of parallel identical machines integrated with an automatic material handling system and it runs fully automatically. Each machine has a same cutting tool configuration that consists of different geometrical cutting tool types on each tool magazine. The job usually takes two stages. Each stage has sequential operations allocated to machines considering the cutting tool life. In the real situation, the cutting tool can fail before the cutting tool life is reached. The objective in this paper is to develop a dynamic scheduling algorithm when a cutting tool is broken during unmanned and a rescheduling needed. The algorithm consists of four steps. The first step is generating initial schedule, the second step is determination the cutting tool failure time, the third step is determination of system status at cutting tool failure time and the fourth step is the rescheduling for unfinished jobs. The approaches to solve the problem are complete-reactive scheduling and robust-proactive scheduling. The new schedules result differences starting time and completion time of each operations from the initial schedule.

  13. Investigations of Effect of Rotary EDM Electrode on Machining Performance of Al6061 Alloy

    NASA Astrophysics Data System (ADS)

    Robinson Smart, D. S.; Jenish Smart, Joses; Periasamy, C.; Ratna Kumar, P. S. Samuel

    2018-04-01

    Electric Discharge Machining is an essential process which is being used for machining desired shape using electrical discharges which creates sparks. There will be electrodes subjected to electric voltage and which are separated by a dielectric liquid. Removing of material will be due to the continuous and rapid current discharges between two electrodes.. The spark is very carefully controlled and localized so that it only affects the surface of the material. Usually in order to prevent the defects which are arising due to the conventional machining, the Electric Discharge Machining (EDM) machining is preferred. Also intricate and complicated shapes can be machined effectively by use of Electric Discharge Machining (EDM). The EDM process usually does not affect the heat treat below the surface. This research work focus on the design and fabrication of rotary EDM tool for machining Al6061alloy and investigation of effect of rotary tool on surface finish, material removal rate and tool wear rate. Also the effect of machining parameters of EDM such as pulse on & off time, current on material Removal Rate (MRR), Surface Roughness (SR) and Electrode wear rate (EWR) have studied. Al6061 alloy can be used for marine and offshore applications by reinforcing some other elements. The investigations have revealed that MRR (material removal rate), surface roughness (Ra) have been improved with the reduction in the tool wear rate (TWR) when the tool is rotating instead of stationary. It was clear that as rotary speed of the tool is increasing the material removal rate is increasing with the reduction of surface finish and tool wear rate.

  14. Machine learning for micro-tomography

    NASA Astrophysics Data System (ADS)

    Parkinson, Dilworth Y.; Pelt, Daniël. M.; Perciano, Talita; Ushizima, Daniela; Krishnan, Harinarayan; Barnard, Harold S.; MacDowell, Alastair A.; Sethian, James

    2017-09-01

    Machine learning has revolutionized a number of fields, but many micro-tomography users have never used it for their work. The micro-tomography beamline at the Advanced Light Source (ALS), in collaboration with the Center for Applied Mathematics for Energy Research Applications (CAMERA) at Lawrence Berkeley National Laboratory, has now deployed a series of tools to automate data processing for ALS users using machine learning. This includes new reconstruction algorithms, feature extraction tools, and image classification and recommen- dation systems for scientific image. Some of these tools are either in automated pipelines that operate on data as it is collected or as stand-alone software. Others are deployed on computing resources at Berkeley Lab-from workstations to supercomputers-and made accessible to users through either scripting or easy-to-use graphical interfaces. This paper presents a progress report on this work.

  15. Metalworking and machining fluids

    DOEpatents

    Erdemir, Ali; Sykora, Frank; Dorbeck, Mark

    2010-10-12

    Improved boron-based metal working and machining fluids. Boric acid and boron-based additives that, when mixed with certain carrier fluids, such as water, cellulose and/or cellulose derivatives, polyhydric alcohol, polyalkylene glycol, polyvinyl alcohol, starch, dextrin, in solid and/or solvated forms result in improved metalworking and machining of metallic work pieces. Fluids manufactured with boric acid or boron-based additives effectively reduce friction, prevent galling and severe wear problems on cutting and forming tools.

  16. Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

    DOE PAGES

    Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

    2017-04-26

    Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

  17. Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

    Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

  18. Application of design sensitivity analysis for greater improvement on machine structural dynamics

    NASA Technical Reports Server (NTRS)

    Yoshimura, Masataka

    1987-01-01

    Methodologies are presented for greatly improving machine structural dynamics by using design sensitivity analyses and evaluative parameters. First, design sensitivity coefficients and evaluative parameters of structural dynamics are described. Next, the relations between the design sensitivity coefficients and the evaluative parameters are clarified. Then, design improvement procedures of structural dynamics are proposed for the following three cases: (1) addition of elastic structural members, (2) addition of mass elements, and (3) substantial charges of joint design variables. Cases (1) and (2) correspond to the changes of the initial framework or configuration, and (3) corresponds to the alteration of poor initial design variables. Finally, numerical examples are given for demonstrating the availability of the methods proposed.

  19. Surface dimpling on rotating work piece using rotation cutting tool

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bhapkar, Rohit Arun; Larsen, Eric Richard

    A combined method of machining and applying a surface texture to a work piece and a tool assembly that is capable of machining and applying a surface texture to a work piece are disclosed. The disclosed method includes machining portions of an outer or inner surface of a work piece. The method also includes rotating the work piece in front of a rotating cutting tool and engaging the outer surface of the work piece with the rotating cutting tool to cut dimples in the outer surface of the work piece. The disclosed tool assembly includes a rotating cutting tool coupledmore » to an end of a rotational machining device, such as a lathe. The same tool assembly can be used to both machine the work piece and apply a surface texture to the work piece without unloading the work piece from the tool assembly.« less

  20. New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

    Treesearch

    L.R. Iverson; A.M. Prasad; A. Liaw

    2004-01-01

    More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

  1. Study on lean thinking among MSMEs in the Machine tool sector in India

    NASA Astrophysics Data System (ADS)

    Priyaadarshini, R. G.; Sathish Kumar, V. R.; Aishwarya Rajlakshmi, S.

    2018-02-01

    In the era of stiff competition and customer expectations, manufacturing organizations across the world are struggling hard to minimize their costs and maximise their performance. Micro, Small and Medium enterprises (MSMEs), who are dependent on large corporate for business and support have a tall task of keeping pace quality in processes and output. They are in the constant vigil to adopt new systems and practices so that they can minimise their cost and maximize the productivity. This study has been conducted in the machine tool sector of Coimbatore, India; which houses more than 9000 companies and offers employment to over one lakh employees. They have a tremendous pressure to use scientific processes to increase their product quality and productivity. While Lean manufacturing has been the thrust to improve the competitiveness among MSMEs in India, this study has attempted to understand their attitude towards lean management and understand the extent to which companies practice lean tools and practices. It has been found that most of the organizations in the study possess a culture of lean thinking and possess the support of top management and employees also towards the initiative. It is also seen that the organizations that incorporated lean in their daily operations have been able to scale up their productivity.

  2. Electrical contact tool set station

    DOEpatents

    Byers, M.E.

    1988-02-22

    An apparatus is provided for the precise setting to zero of electrically conductive cutting tools used in the machining of work pieces. An electrically conductive cylindrical pin, tapered at one end to a small flat, rests in a vee-shaped channel in a base so that its longitudinal axis is parallel to the longitudinal axis of the machine's spindle. Electronic apparatus is connected between the cylindrical pin and the electrically conductive cutting tool to produce a detectable signal when contact between tool and pin is made. The axes of the machine are set to zero by contact between the cutting tool and the sides, end or top of the cylindrical pin. Upon contact, an electrical circuit is completed, and the detectable signal is produced. The tool can then be set to zero for that axis. Should the tool contact the cylindrical pin with too much force, the cylindrical pin would be harmlessly dislodged from the vee-shaped channel, preventing damage either to the cutting tool or the cylindrical pin. 5 figs.

  3. Machine-learning-assisted materials discovery using failed experiments

    NASA Astrophysics Data System (ADS)

    Raccuglia, Paul; Elbert, Katherine C.; Adler, Philip D. F.; Falk, Casey; Wenny, Malia B.; Mollo, Aurelio; Zeller, Matthias; Friedler, Sorelle A.; Schrier, Joshua; Norquist, Alexander J.

    2016-05-01

    Inorganic-organic hybrid materials such as organically templated metal oxides, metal-organic frameworks (MOFs) and organohalide perovskites have been studied for decades, and hydrothermal and (non-aqueous) solvothermal syntheses have produced thousands of new materials that collectively contain nearly all the metals in the periodic table. Nevertheless, the formation of these compounds is not fully understood, and development of new compounds relies primarily on exploratory syntheses. Simulation- and data-driven approaches (promoted by efforts such as the Materials Genome Initiative) provide an alternative to experimental trial-and-error. Three major strategies are: simulation-based predictions of physical properties (for example, charge mobility, photovoltaic properties, gas adsorption capacity or lithium-ion intercalation) to identify promising target candidates for synthetic efforts; determination of the structure-property relationship from large bodies of experimental data, enabled by integration with high-throughput synthesis and measurement tools; and clustering on the basis of similar crystallographic structure (for example, zeolite structure classification or gas adsorption properties). Here we demonstrate an alternative approach that uses machine-learning algorithms trained on reaction data to predict reaction outcomes for the crystallization of templated vanadium selenites. We used information on ‘dark’ reactions—failed or unsuccessful hydrothermal syntheses—collected from archived laboratory notebooks from our laboratory, and added physicochemical property descriptions to the raw notebook information using cheminformatics techniques. We used the resulting data to train a machine-learning model to predict reaction success. When carrying out hydrothermal synthesis experiments using previously untested, commercially available organic building blocks, our machine-learning model outperformed traditional human strategies, and successfully predicted

  4. Cutting Zone Temperature Identification During Machining of Nickel Alloy Inconel 718

    NASA Astrophysics Data System (ADS)

    Czán, Andrej; Daniš, Igor; Holubják, Jozef; Zaušková, Lucia; Czánová, Tatiana; Mikloš, Matej; Martikáň, Pavol

    2017-12-01

    Quality of machined surface is affected by quality of cutting process. There are many parameters, which influence on the quality of the cutting process. The cutting temperature is one of most important parameters that influence the tool life and the quality of machined surfaces. Its identification and determination is key objective in specialized machining processes such as dry machining of hard-to-machine materials. It is well known that maximum temperature is obtained in the tool rake face at the vicinity of the cutting edge. A moderate level of cutting edge temperature and a low thermal shock reduce the tool wear phenomena, and a low temperature gradient in the machined sublayer reduces the risk of high tensile residual stresses. The thermocouple method was used to measure the temperature directly in the cutting zone. An original thermocouple was specially developed for measuring of temperature in the cutting zone, surface and subsurface layers of machined surface. This paper deals with identification of temperature and temperature gradient during dry peripheral milling of Inconel 718. The measurements were used to identification the temperature gradients and to reconstruct the thermal distribution in cutting zone with various cutting conditions.

  5. Osteoporosis risk prediction using machine learning and conventional methods.

    PubMed

    Kim, Sung Kean; Yoo, Tae Keun; Oh, Ein; Kim, Deok Won

    2013-01-01

    A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women, and compared with the ability of a conventional clinical decision tool, osteoporosis self-assessment tool (OST). We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Surveys (KNHANES V-1). The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests (RF), artificial neural networks (ANN), and logistic regression (LR) based on various predictors associated with low bone density. The learning models were compared with OST. SVM had significantly better area under the curve (AUC) of the receiver operating characteristic (ROC) than ANN, LR, and OST. Validation on the test set showed that SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0%. We were the first to perform comparisons of the performance of osteoporosis prediction between the machine learning and conventional methods using population-based epidemiological data. The machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

  6. Machine-Learned Data Structures of Lipid Marker Serum Concentrations in Multiple Sclerosis Patients Differ from Those in Healthy Subjects.

    PubMed

    Lötsch, Jörn; Thrun, Michael; Lerch, Florian; Brunkhorst, Robert; Schiffmann, Susanne; Thomas, Dominique; Tegder, Irmgard; Geisslinger, Gerd; Ultsch, Alfred

    2017-06-07

    Lipid metabolism has been suggested to be a major pathophysiological mechanism of multiple sclerosis (MS). With the increasing knowledge about lipid signaling, acquired data become increasingly complex making bioinformatics necessary in lipid research. We used unsupervised machine-learning to analyze lipid marker serum concentrations, pursuing the hypothesis that for the most relevant markers the emerging data structures will coincide with the diagnosis of MS. Machine learning was implemented as emergent self-organizing feature maps (ESOM) combined with the U*-matrix visualization technique. The data space consisted of serum concentrations of three main classes of lipid markers comprising eicosanoids ( d = 11 markers), ceramides ( d = 10), and lyosophosphatidic acids ( d = 6). They were analyzed in cohorts of MS patients ( n = 102) and healthy subjects ( n = 301). Clear data structures in the high-dimensional data space were observed in eicosanoid and ceramides serum concentrations whereas no clear structure could be found in lysophosphatidic acid concentrations. With ceramide concentrations, the structures that had emerged from unsupervised machine-learning almost completely overlapped with the known grouping of MS patients versus healthy subjects. This was only partly provided by eicosanoid serum concentrations. Thus, unsupervised machine-learning identified distinct data structures of bioactive lipid serum concentrations. These structures could be superimposed with the known grouping of MS patients versus healthy subjects, which was almost completely possible with ceramides. Therefore, based on the present analysis, ceramides are first-line candidates for further exploration as drug-gable targets or biomarkers in MS.

  7. Machine-Learned Data Structures of Lipid Marker Serum Concentrations in Multiple Sclerosis Patients Differ from Those in Healthy Subjects

    PubMed Central

    Lötsch, Jörn; Thrun, Michael; Lerch, Florian; Brunkhorst, Robert; Schiffmann, Susanne; Thomas, Dominique; Tegder, Irmgard; Geisslinger, Gerd; Ultsch, Alfred

    2017-01-01

    Lipid signaling has been suggested to be a major pathophysiological mechanism of multiple sclerosis (MS). With the increasing knowledge about lipid signaling, acquired data become increasingly complex making bioinformatics necessary in lipid research. We used unsupervised machine-learning to analyze lipid marker serum concentrations, pursuing the hypothesis that for the most relevant markers the emerging data structures will coincide with the diagnosis of MS. Machine learning was implemented as emergent self-organizing feature maps (ESOM) combined with the U*-matrix visualization technique. The data space consisted of serum concentrations of three main classes of lipid markers comprising eicosanoids (d = 11 markers), ceramides (d = 10), and lyosophosphatidic acids (d = 6). They were analyzed in cohorts of MS patients (n = 102) and healthy subjects (n = 301). Clear data structures in the high-dimensional data space were observed in eicosanoid and ceramides serum concentrations whereas no clear structure could be found in lysophosphatidic acid concentrations. With ceramide concentrations, the structures that had emerged from unsupervised machine-learning almost completely overlapped with the known grouping of MS patients versus healthy subjects. This was only partly provided by eicosanoid serum concentrations. Thus, unsupervised machine-learning identified distinct data structures of bioactive lipid serum concentrations. These structures could be superimposed with the known grouping of MS patients versus healthy subjects, which was almost completely possible with ceramides. Therefore, based on the present analysis, ceramides are first-line candidates for further exploration as drug-gable targets or biomarkers in MS. PMID:28590455

  8. Using support vector machines to improve elemental ion identification in macromolecular crystal structures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Morshed, Nader; Lawrence Berkeley National Laboratory, Berkeley, CA 94720; Echols, Nathaniel, E-mail: nechols@lbl.gov

    2015-05-01

    A method to automatically identify possible elemental ions in X-ray crystal structures has been extended to use support vector machine (SVM) classifiers trained on selected structures in the PDB, with significantly improved sensitivity over manually encoded heuristics. In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific knowledge of metal-binding chemistry and scattering properties and is prone to error. A method has previously been described to identify ions based on manually chosen criteria for a number of elements. Here,more » the use of support vector machines (SVMs) to automatically classify isolated atoms as either solvent or one of various ions is described. Two data sets of protein crystal structures, one containing manually curated structures deposited with anomalous diffraction data and another with automatically filtered, high-resolution structures, were constructed. On the manually curated data set, an SVM classifier was able to distinguish calcium from manganese, zinc, iron and nickel, as well as all five of these ions from water molecules, with a high degree of accuracy. Additionally, SVMs trained on the automatically curated set of high-resolution structures were able to successfully classify most common elemental ions in an independent validation test set. This method is readily extensible to other elemental ions and can also be used in conjunction with previous methods based on a priori expectations of the chemical environment and X-ray scattering.« less

  9. [Present-day metal-cutting tools and working conditions].

    PubMed

    Kondratiuk, V P

    1990-01-01

    Polyfunctional machine-tools of a processing centre type are characterized by a set of hygienic advantages as compared to universal machine-tools. But low degree of mechanization and automation of some auxiliary processes, and constructional defects which decrease the ergonomic characteristics of the tools, involve labour intensity in multi-machine processing. The article specifies techniques of allowable noise level assessment, and proposes hygienic recommendations, some of which have been introduced into practice.

  10. Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

    PubMed

    Lu, Xiaobing; Yang, Yongzhe; Wu, Fengchun; Gao, Minjian; Xu, Yong; Zhang, Yue; Yao, Yongcheng; Du, Xin; Li, Chengwei; Wu, Lei; Zhong, Xiaomei; Zhou, Yanling; Fan, Ni; Zheng, Yingjun; Xiong, Dongsheng; Peng, Hongjun; Escudero, Javier; Huang, Biao; Li, Xiaobo; Ning, Yuping; Wu, Kai

    2016-07-01

    Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

  11. Sustainable cooling method for machining titanium alloy

    NASA Astrophysics Data System (ADS)

    Boswell, B.; Islam, M. N.

    2016-02-01

    Hard to machine materials such as Titanium Alloy TI-6AI-4V Grade 5 are notoriously known to generate high temperatures and adverse reactions between the workpiece and the tool tip materials. These conditions all contribute to an increase in the wear mechanisms, reducing tool life. Titanium Alloy, for example always requires coolant to be used during machining. However, traditional flood cooling needs to be replaced due to environmental issues, and an alternative cooling method found that has minimum impact on the environment. For true sustainable cooling of the tool it is necessary to account for all energy used in the cooling process, including the energy involved in producing the coolant. Previous research has established that efficient cooling of the tool interface improves the tool life and cutting action. The objective of this research is to determine the most appropriate sustainable cooling method that can also reduce the rate of wear at the tool interface.

  12. Manifold learning in machine vision and robotics

    NASA Astrophysics Data System (ADS)

    Bernstein, Alexander

    2017-02-01

    Smart algorithms are used in Machine vision and Robotics to organize or extract high-level information from the available data. Nowadays, Machine learning is an essential and ubiquitous tool to automate extraction patterns or regularities from data (images in Machine vision; camera, laser, and sonar sensors data in Robotics) in order to solve various subject-oriented tasks such as understanding and classification of images content, navigation of mobile autonomous robot in uncertain environments, robot manipulation in medical robotics and computer-assisted surgery, and other. Usually such data have high dimensionality, however, due to various dependencies between their components and constraints caused by physical reasons, all "feasible and usable data" occupy only a very small part in high dimensional "observation space" with smaller intrinsic dimensionality. Generally accepted model of such data is manifold model in accordance with which the data lie on or near an unknown manifold (surface) of lower dimensionality embedded in an ambient high dimensional observation space; real-world high-dimensional data obtained from "natural" sources meet, as a rule, this model. The use of Manifold learning technique in Machine vision and Robotics, which discovers a low-dimensional structure of high dimensional data and results in effective algorithms for solving of a large number of various subject-oriented tasks, is the content of the conference plenary speech some topics of which are in the paper.

  13. Analysis about diamond tool wear in nano-metric cutting of single crystal silicon using molecular dynamics method

    NASA Astrophysics Data System (ADS)

    Wang, Zhiguo; Liang, Yingchun; Chen, Mingjun; Tong, Zhen; Chen, Jiaxuan

    2010-10-01

    Tool wear not only changes its geometry accuracy and integrity, but also decrease machining precision and surface integrity of workpiece that affect using performance and service life of workpiece in ultra-precision machining. Scholars made a lot of experimental researches and stimulant analyses, but there is a great difference on the wear mechanism, especially on the nano-scale wear mechanism. In this paper, the three-dimensional simulation model is built to simulate nano-metric cutting of a single crystal silicon with a non-rigid right-angle diamond tool with 0 rake angle and 0 clearance angle by the molecular dynamics (MD) simulation approach, which is used to investigate the diamond tool wear during the nano-metric cutting process. A Tersoff potential is employed for the interaction between carbon-carbon atoms, silicon-silicon atoms and carbon-silicon atoms. The tool gets the high alternating shear stress, the tool wear firstly presents at the cutting edge where intension is low. At the corner the tool is splitted along the {1 1 1} crystal plane, which forms the tipping. The wear at the flank face is the structure transformation of diamond that the diamond structure transforms into the sheet graphite structure. Owing to the tool wear the cutting force increases.

  14. CNC Machining Of The Complex Copper Electrodes

    NASA Astrophysics Data System (ADS)

    Popan, Ioan Alexandru; Balc, Nicolae; Popan, Alina

    2015-07-01

    This paper presents the machining process of the complex copper electrodes. Machining of the complex shapes in copper is difficult because this material is soft and sticky. This research presents the main steps for processing those copper electrodes at a high dimensional accuracy and a good surface quality. Special tooling solutions are required for this machining process and optimal process parameters have been found for the accurate CNC equipment, using smart CAD/CAM software.

  15. Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining

    PubMed Central

    Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

    2016-01-01

    Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing. PMID:27854322

  16. Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining.

    PubMed

    Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

    2016-11-16

    Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

  17. Investigation of approximate models of experimental temperature characteristics of machines

    NASA Astrophysics Data System (ADS)

    Parfenov, I. V.; Polyakov, A. N.

    2018-05-01

    This work is devoted to the investigation of various approaches to the approximation of experimental data and the creation of simulation mathematical models of thermal processes in machines with the aim of finding ways to reduce the time of their field tests and reducing the temperature error of the treatments. The main methods of research which the authors used in this work are: the full-scale thermal testing of machines; realization of various approaches at approximation of experimental temperature characteristics of machine tools by polynomial models; analysis and evaluation of modelling results (model quality) of the temperature characteristics of machines and their derivatives up to the third order in time. As a result of the performed researches, rational methods, type, parameters and complexity of simulation mathematical models of thermal processes in machine tools are proposed.

  18. Technical Report on Occupations in Numerically Controlled Metal-Cutting Machining.

    ERIC Educational Resources Information Center

    Manpower Administration (DOL), Washington, DC. U.S. Employment Service.

    At the present time, only 5 percent of the short-run metal-cutting machining in the United States is done by numerically controlled machined tools, but within the next decade it is expected to increase by 50 percent. Numerically controlled machines use taped data which is changed into instructions and directs the machine to do certain steps…

  19. Development of a State Machine Sequencer for the Keck Interferometer: Evolution, Development and Lessons Learned using a CASE Tool Approach

    NASA Technical Reports Server (NTRS)

    Rede, Leonard J.; Booth, Andrew; Hsieh, Jonathon; Summer, Kellee

    2004-01-01

    This paper presents a discussion of the evolution of a sequencer from a simple EPICS (Experimental Physics and Industrial Control System) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a CASE (Computer Aided Software Engineering) tool approach. The main purpose of the sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Hare1 finite state machine, software program designed to orchestrate several lower-level hardware and software hard real time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORB A, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

  20. Development of a state machine sequencer for the Keck Interferometer: evolution, development, and lessons learned using a CASE tool approach

    NASA Astrophysics Data System (ADS)

    Reder, Leonard J.; Booth, Andrew; Hsieh, Jonathan; Summers, Kellee R.

    2004-09-01

    This paper presents a discussion of the evolution of a sequencer from a simple Experimental Physics and Industrial Control System (EPICS) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a Computer Aided Software Engineering (CASE) tool approach. The main purpose of the Interferometer Sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations to be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Harel finite state machine software program designed to orchestrate several lower-level hardware and software hard real-time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORBA, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

  1. Engineered Surface Properties of Porous Tungsten from Cryogenic Machining

    NASA Astrophysics Data System (ADS)

    Schoop, Julius Malte

    Porous tungsten is used to manufacture dispenser cathodes due to it refractory properties. Surface porosity is critical to functional performance of dispenser cathodes because it allows for an impregnated ceramic compound to migrate to the emitting surface, lowering its work function. Likewise, surface roughness is important because it is necessary to ensure uniform wetting of the molten impregnate during high temperature service. Current industry practice to achieve surface roughness and surface porosity requirements involves the use of a plastic infiltrant during machining. After machining, the infiltrant is baked and the cathode pellet is impregnated. In this context, cryogenic machining is investigated as a substitutionary process for the current plastic infiltration process. Along with significant reductions in cycle time and resource use, surface quality of cryogenically machined un-infiltrated (as-sintered) porous tungsten has been shown to significantly outperform dry machining. The present study is focused on examining the relationship between machining parameters and cooling condition on the as-machined surface integrity of porous tungsten. The effects of cryogenic pre-cooling, rake angle, cutting speed, depth of cut and feed are all taken into consideration with respect to machining-induced surface morphology. Cermet and Polycrystalline diamond (PCD) cutting tools are used to develop high performance cryogenic machining of porous tungsten. Dry and pre-heated machining were investigated as a means to allow for ductile mode machining, yet severe tool-wear and undesirable smearing limited the feasibility of these approaches. By using modified PCD cutting tools, high speed machining of porous tungsten at cutting speeds up to 400 m/min is achieved for the first time. Beyond a critical speed, brittle fracture and built-up edge are eliminated as the result of a brittle to ductile transition. A model of critical chip thickness ( hc ) effects based on cutting

  2. Computer Aided Drafting and Design, Industrial Manufacturing Technician, and Mechanical Engineering Technician and Machine Tool, Die and Moldmaking Technology. Tech Prep Competency Profile.

    ERIC Educational Resources Information Center

    Mid-East Ohio Tech Prep Consortium, Zanesville.

    This document contains competency profiles in four areas: computer-aided drafting and design; industrial manufacturing technician; mechanical engineering technician; and machine tool, die, and moldmaking technology occupations. The profiles are intended for use in articulating tech prep programs from high school through associate degrees in Ohio.…

  3. Depth indicator and stop aid machining to precise tolerances

    NASA Technical Reports Server (NTRS)

    Laverty, J. L.

    1966-01-01

    Attachment for machine tools provides a visual indication of the depth of cut and a positive stop to prevent overcutting. This attachment is used with drill presses, vertical milling machines, and jig borers.

  4. A Machine-to-Machine protocol benchmark for eHealth applications - Use case: Respiratory rehabilitation.

    PubMed

    Talaminos-Barroso, Alejandro; Estudillo-Valderrama, Miguel A; Roa, Laura M; Reina-Tosina, Javier; Ortega-Ruiz, Francisco

    2016-06-01

    M2M (Machine-to-Machine) communications represent one of the main pillars of the new paradigm of the Internet of Things (IoT), and is making possible new opportunities for the eHealth business. Nevertheless, the large number of M2M protocols currently available hinders the election of a suitable solution that satisfies the requirements that can demand eHealth applications. In the first place, to develop a tool that provides a benchmarking analysis in order to objectively select among the most relevant M2M protocols for eHealth solutions. In the second place, to validate the tool with a particular use case: the respiratory rehabilitation. A software tool, called Distributed Computing Framework (DFC), has been designed and developed to execute the benchmarking tests and facilitate the deployment in environments with a large number of machines, with independence of the protocol and performance metrics selected. DDS, MQTT, CoAP, JMS, AMQP and XMPP protocols were evaluated considering different specific performance metrics, including CPU usage, memory usage, bandwidth consumption, latency and jitter. The results obtained allowed to validate a case of use: respiratory rehabilitation of chronic obstructive pulmonary disease (COPD) patients in two scenarios with different types of requirement: Home-Based and Ambulatory. The results of the benchmark comparison can guide eHealth developers in the choice of M2M technologies. In this regard, the framework presented is a simple and powerful tool for the deployment of benchmark tests under specific environments and conditions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. Adaptive machine and its thermodynamic costs

    NASA Astrophysics Data System (ADS)

    Allahverdyan, Armen E.; Wang, Q. A.

    2013-03-01

    We study the minimal thermodynamically consistent model for an adaptive machine that transfers particles from a higher chemical potential reservoir to a lower one. This model describes essentials of the inhomogeneous catalysis. It is supposed to function with the maximal current under uncertain chemical potentials: if they change, the machine tunes its own structure fitting it to the maximal current under new conditions. This adaptation is possible under two limitations: (i) The degree of freedom that controls the machine's structure has to have a stored energy (described via a negative temperature). The origin of this result is traced back to the Le Chatelier principle. (ii) The machine has to malfunction at a constant environment due to structural fluctuations, whose relative magnitude is controlled solely by the stored energy. We argue that several features of the adaptive machine are similar to those of living organisms (energy storage, aging).

  6. MACHINE COOLANT WASTE REDUCTION BY OPTIMIZING COOLANT LIFE

    EPA Science Inventory

    Machine shops use coolants to improve the life and function of machine tools. hese coolants become contaminated with oils with use, and this contamination can lead to growth of anaerobic bacteria and shortened coolant life. his project investigated methods to extend coolant life ...

  7. Machine-learning approach for local classification of crystalline structures in multiphase systems

    NASA Astrophysics Data System (ADS)

    Dietz, C.; Kretz, T.; Thoma, M. H.

    2017-07-01

    Machine learning is one of the most popular fields in computer science and has a vast number of applications. In this work we will propose a method that will use a neural network to locally identify crystal structures in a mixed phase Yukawa system consisting of fcc, hcp, and bcc clusters and disordered particles similar to plasma crystals. We compare our approach to already used methods and show that the quality of identification increases significantly. The technique works very well for highly disturbed lattices and shows a flexible and robust way to classify crystalline structures that can be used by only providing particle positions. This leads to insights into highly disturbed crystalline structures.

  8. Cold machining of high density tungsten and other materials

    NASA Technical Reports Server (NTRS)

    Ziegelmeier, P.

    1969-01-01

    Cold machining process, which uses a sub-zero refrigerated cutting fluid, is used for machining refractory or reactive metals and alloys. Special carbide tools for turning and drilling these alloys further improve the cutting performance.

  9. ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches.

    PubMed

    Sharma, Ashok K; Srivastava, Gopal N; Roy, Ankita; Sharma, Vineet K

    2017-01-01

    The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93%) and Matthews's correlation coefficient (0.84). The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84-0.87) on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better ( R 2 = 0.84) than the multi-linear regression (MLR) and partial least square regression (PLSR) models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2) performed better ( R 2 = 0.68) in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity

  10. ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches

    PubMed Central

    Sharma, Ashok K.; Srivastava, Gopal N.; Roy, Ankita; Sharma, Vineet K.

    2017-01-01

    The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93%) and Matthews's correlation coefficient (0.84). The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84–0.87) on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better (R2 = 0.84) than the multi-linear regression (MLR) and partial least square regression (PLSR) models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2) performed better (R2 = 0.68) in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity, solubility

  11. Machinability of CAD-CAM materials.

    PubMed

    Chavali, Ramakiran; Nejat, Amir H; Lawson, Nathaniel C

    2017-08-01

    Although new materials are available for computer-aided design and computer-aided manufacturing (CAD-CAM) fabrication, limited information is available regarding their machinability. The depth of penetration of a milling tool into a material during a timed milling cycle may indicate its machinability. The purpose of this in vitro study was to compare the tool penetration rate for 2 polymer-containing CAD-CAM materials (Lava Ultimate and Enamic) and 2 ceramic-based CAD-CAM materials (e.max CAD and Celtra Duo). The materials were sectioned into 4-mm-thick specimens (n=5/material) and polished with 320-grit SiC paper. Each specimen was loaded into a custom milling apparatus. The apparatus pushed the specimens against a milling tool (E4D Tapered 2016000) rotating at 40 000 RPM with a constant force of 0.98 N. After a 6-minute timed milling cycle, the length of each milling cut was measured with image analysis software under a digital light microscope. Representative specimens and milling tools were examined with scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy. The penetration rate of Lava Ultimate (3.21 ±0.46 mm/min) and Enamic (2.53 ±0.57 mm/min) was significantly greater than that of e.max CAD (1.12 ±0.32 mm/min) or Celtra Duo (0.80 ±0.21 mm/min) materials. SEM observations showed little tool damage, regardless of material type. Residual material was found on the tools used with polymer-containing materials, and wear of the embedding medium was seen on the tools used with the ceramic-based materials. Edge chipping was noted on cuts made in the ceramic-based materials. Lava Ultimate and Enamic have greater machinability and less edge chipping than e.max CAD and Celtra Duo. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

  12. SKYNET: an efficient and robust neural network training tool for machine learning in astronomy

    NASA Astrophysics Data System (ADS)

    Graff, Philip; Feroz, Farhan; Hobson, Michael P.; Lasenby, Anthony

    2014-06-01

    We present the first public release of our generic neural network training algorithm, called SKYNET. This efficient and robust machine learning tool is able to train large and deep feed-forward neural networks, including autoencoders, for use in a wide range of supervised and unsupervised learning applications, such as regression, classification, density estimation, clustering and dimensionality reduction. SKYNET uses a `pre-training' method to obtain a set of network parameters that has empirically been shown to be close to a good solution, followed by further optimization using a regularized variant of Newton's method, where the level of regularization is determined and adjusted automatically; the latter uses second-order derivative information to improve convergence, but without the need to evaluate or store the full Hessian matrix, by using a fast approximate method to calculate Hessian-vector products. This combination of methods allows for the training of complicated networks that are difficult to optimize using standard backpropagation techniques. SKYNET employs convergence criteria that naturally prevent overfitting, and also includes a fast algorithm for estimating the accuracy of network outputs. The utility and flexibility of SKYNET are demonstrated by application to a number of toy problems, and to astronomical problems focusing on the recovery of structure from blurred and noisy images, the identification of gamma-ray bursters, and the compression and denoising of galaxy images. The SKYNET software, which is implemented in standard ANSI C and fully parallelized using MPI, is available at http://www.mrao.cam.ac.uk/software/skynet/.

  13. A Boltzmann machine for the organization of intelligent machines

    NASA Technical Reports Server (NTRS)

    Moed, Michael C.; Saridis, George N.

    1990-01-01

    A three-tier structure consisting of organization, coordination, and execution levels forms the architecture of an intelligent machine using the principle of increasing precision with decreasing intelligence from a hierarchically intelligent control. This system has been formulated as a probabilistic model, where uncertainty and imprecision can be expressed in terms of entropies. The optimal strategy for decision planning and task execution can be found by minimizing the total entropy in the system. The focus is on the design of the organization level as a Boltzmann machine. Since this level is responsible for planning the actions of the machine, the Boltzmann machine is reformulated to use entropy as the cost function to be minimized. Simulated annealing, expanding subinterval random search, and the genetic algorithm are presented as search techniques to efficiently find the desired action sequence and illustrated with numerical examples.

  14. Method of fabricating a micro machine

    DOEpatents

    Stalford, Harold L

    2014-11-11

    A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

  15. Methods and systems for micro machines

    DOEpatents

    Stalford, Harold L.

    2018-03-06

    A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

  16. Methods and systems for micro machines

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Stalford, Harold L.

    2017-04-11

    A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

  17. Methods and systems for micro machines

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Stalford, Harold L.

    A micro machine may be in or less than the micrometer domain. The micro machine may include a micro actuator and a micro shaft coupled to the micro actuator. The micro shaft is operable to be driven by the micro actuator. A tool is coupled to the micro shaft and is operable to perform work in response to at least motion of the micro shaft.

  18. Evolutionary algorithm based optimization of hydraulic machines utilizing a state-of-the-art block coupled CFD solver and parametric geometry and mesh generation tools

    NASA Astrophysics Data System (ADS)

    S, Kyriacou; E, Kontoleontos; S, Weissenberger; L, Mangani; E, Casartelli; I, Skouteropoulou; M, Gattringer; A, Gehrer; M, Buchmayr

    2014-03-01

    An efficient hydraulic optimization procedure, suitable for industrial use, requires an advanced optimization tool (EASY software), a fast solver (block coupled CFD) and a flexible geometry generation tool. EASY optimization software is a PCA-driven metamodel-assisted Evolutionary Algorithm (MAEA (PCA)) that can be used in both single- (SOO) and multiobjective optimization (MOO) problems. In MAEAs, low cost surrogate evaluation models are used to screen out non-promising individuals during the evolution and exclude them from the expensive, problem specific evaluation, here the solution of Navier-Stokes equations. For additional reduction of the optimization CPU cost, the PCA technique is used to identify dependences among the design variables and to exploit them in order to efficiently drive the application of the evolution operators. To further enhance the hydraulic optimization procedure, a very robust and fast Navier-Stokes solver has been developed. This incompressible CFD solver employs a pressure-based block-coupled approach, solving the governing equations simultaneously. This method, apart from being robust and fast, also provides a big gain in terms of computational cost. In order to optimize the geometry of hydraulic machines, an automatic geometry and mesh generation tool is necessary. The geometry generation tool used in this work is entirely based on b-spline curves and surfaces. In what follows, the components of the tool chain are outlined in some detail and the optimization results of hydraulic machine components are shown in order to demonstrate the performance of the presented optimization procedure.

  19. Programmable phase plate for tool modification in laser machining applications

    DOEpatents

    Thompson Jr., Charles A.; Kartz, Michael W.; Brase, James M.; Pennington, Deanna; Perry, Michael D.

    2004-04-06

    A system for laser machining includes a laser source for propagating a laser beam toward a target location, and a spatial light modulator having individual controllable elements capable of modifying a phase profile of the laser beam to produce a corresponding irradiance pattern on the target location. The system also includes a controller operably connected to the spatial light modulator for controlling the individual controllable elements. By controlling the individual controllable elements, the phase profile of the laser beam may be modified into a desired phase profile so as to produce a corresponding desired irradiance pattern on the target location capable of performing a machining operation on the target location.

  20. [Comparison of machinability of two types of dental machinable ceramic].

    PubMed

    Fu, Qiang; Zhao, Yunfeng; Li, Yong; Fan, Xinping; Li, Yan; Lin, Xuefeng

    2002-11-01

    In terms of the problems of now available dental machinable ceramics, a new type of calcium-mica glass-ceramic, PMC-I ceramic, was developed, and its machinability was compared with that of Vita MKII quantitatively. Moreover, the relationship between the strength and the machinability of PMC-I ceramic was studied. Samples of PMC-I ceramic were divided into four groups according to their nucleation procedures. 600-seconds drilling tests were conducted with high-speed steel tools (Phi = 2.3 mm) to measure the drilling depths of Vita MKII ceramic and PMC-I ceramic, while constant drilling speed of 600 rpm and constant axial load of 39.2 N were used. And the 3-point bending strength of the four groups of PMC-I ceramic were recorded. Drilling depth of Vita MKII was 0.71 mm, while the depths of the four groups of PMC-I ceramic were 0.88 mm, 1.40 mm, 0.40 mm and 0.90 mm, respectively. Group B of PMC-I ceramic showed the largest depth of 1.40 mm and was statistically different from other groups and Vita MKII. And the strength of the four groups of PMC-I ceramic were 137.7, 210.2, 118.0 and 106.0 MPa, respectively. The machinability of the new developed dental machinable ceramic of PMC-I could meet the need of the clinic.

  1. Learning surface molecular structures via machine vision

    NASA Astrophysics Data System (ADS)

    Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

    2017-08-01

    Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (`read out') all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. The method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

  2. Learning surface molecular structures via machine vision

    DOE PAGES

    Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

    2017-08-10

    Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (‘read out’) all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds andmore » thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. Here, the method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.« less

  3. Learning surface molecular structures via machine vision

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

    Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (‘read out’) all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds andmore » thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. Here, the method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.« less

  4. Technology of high-speed combined machining with brush electrode

    NASA Astrophysics Data System (ADS)

    Kirillov, O. N.; Smolentsev, V. P.; Yukhnevich, S. S.

    2018-03-01

    The new method was proposed for high-precision dimensional machining with a brush electrode when the true position of bundles of metal wire is adjusted by means of creating controlled centrifugal forces appeared due to the increased frequency of rotation of a tool. There are the ultimate values of circumferential velocity at which the bundles are pressed against a machined area of a workpiece in a stable manner despite the profile of the machined surface and variable stock of the workpiece. The special aspects of design of processing procedures for finishing standard parts, including components of products with low rigidity, are disclosed. The methodology of calculation and selection of processing modes which allow one to produce high-precision details and to provide corresponding surface roughness required to perform finishing operations (including the preparation of a surface for metal deposition) is presented. The production experience concerned with the use of high-speed combined machining with an unshaped tool electrode in knowledge-intensive branches of the machine-building industry for different types of production is analyzed. It is shown that the implementation of high-speed dimensional machining with an unshaped brush electrode allows one to expand the field of use of the considered process due to the application of a multipurpose tool in the form of a metal brush, as well as to obtain stable results of finishing and to provide the opportunities for long-term operation of the equipment without its changeover and readjustment.

  5. Process Approach for Modeling of Machine and Tractor Fleet Structure

    NASA Astrophysics Data System (ADS)

    Dokin, B. D.; Aletdinova, A. A.; Kravchenko, M. S.; Tsybina, Y. S.

    2018-05-01

    The existing software complexes on modelling of the machine and tractor fleet structure are mostly aimed at solving the task of optimization. However, the creators, choosing only one optimization criterion and incorporating it in their software, provide grounds on why it is the best without giving a decision maker the opportunity to choose it for their enterprise. To analyze “bottlenecks” of machine and tractor fleet modelling, the authors of this article created a process model, in which they included adjustment to the plan of using machinery based on searching through alternative technologies. As a result, the following recommendations for software complex development have been worked out: the introduction of a database of alternative technologies; the possibility for a user to change the timing of the operations even beyond the allowable limits and in that case the calculation of the incurred loss; the possibility to rule out the solution of an optimization task, and if there is a necessity in it - the possibility to choose an optimization criterion; introducing graphical display of an annual complex of works, which could be enough for the development and adjustment of a business strategy.

  6. A Machine Learning and Optimization Toolkit for the Swarm

    DTIC Science & Technology

    2014-11-17

    Machine   Learning  and  Op0miza0on   Toolkit  for  the  Swarm   Ilge  Akkaya,  Shuhei  Emoto...3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE A Machine Learning and Optimization Toolkit for the Swarm 5a. CONTRACT NUMBER... machine   learning   methodologies  by  providing  the  right  interfaces  between   machine   learning  tools  and

  7. Comparative Investigation on Tool Wear during End Milling of AISI H13 Steel with Different Tool Path Strategies

    NASA Astrophysics Data System (ADS)

    Adesta, Erry Yulian T.; Riza, Muhammad; Avicena

    2018-03-01

    Tool wear prediction plays a significant role in machining industry for proper planning and control machining parameters and optimization of cutting conditions. This paper aims to investigate the effect of tool path strategies that are contour-in and zigzag tool path strategies applied on tool wear during pocket milling process. The experiments were carried out on CNC vertical machining centre by involving PVD coated carbide inserts. Cutting speed, feed rate and depth of cut were set to vary. In an experiment with three factors at three levels, Response Surface Method (RSM) design of experiment with a standard called Central Composite Design (CCD) was employed. Results obtained indicate that tool wear increases significantly at higher range of feed per tooth compared to cutting speed and depth of cut. This result of this experimental work is then proven statistically by developing empirical model. The prediction model for the response variable of tool wear for contour-in strategy developed in this research shows a good agreement with experimental work.

  8. Looking west at Machine Shop (Bldg. 163) south bay interior. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Looking west at Machine Shop (Bldg. 163) south bay interior. Note the Shaw 15-ton bridge crane. This portion of the building housed machine tools and locomotive component repair functions that supported the erecting shop operations - Atchison, Topeka, Santa Fe Railroad, Albuquerque Shops, Machine Shop, 908 Second Street, Southwest, Albuquerque, Bernalillo County, NM

  9. Intelligent image processing for machine safety

    NASA Astrophysics Data System (ADS)

    Harvey, Dennis N.

    1994-10-01

    This paper describes the use of intelligent image processing as a machine guarding technology. One or more color, linear array cameras are positioned to view the critical region(s) around a machine tool or other piece of manufacturing equipment. The image data is processed to provide indicators of conditions dangerous to the equipment via color content, shape content, and motion content. The data from these analyses is then sent to a threat evaluator. The purpose of the evaluator is to determine if a potentially machine-damaging condition exists based on the analyses of color, shape, and motion, and on `knowledge' of the specific environment of the machine. The threat evaluator employs fuzzy logic as a means of dealing with uncertainty in the vision data.

  10. Industrial machine systems risk assessment: a critical review of concepts and methods.

    PubMed

    Etherton, John R

    2007-02-01

    Reducing the risk of work-related death and injury to machine operators and maintenance personnel poses a continuing occupational safety challenge. The risk of injury from machinery in U.S. workplaces is high. Between 1992 and 2001, there were, on average, 520 fatalities per year involving machines and, on average, 3.8 cases per 10,000 workers of nonfatal caught-in-running-machine injuries involving lost workdays. A U.S. task group recently developed a technical reference guideline, ANSI B11 TR3, "A Guide to Estimate, Evaluate, & Reduce Risks Associated with Machine Tools," that is intended to bring machine tool risk assessment practice in the United States up to or above the level now required by the international standard, ISO 14121. The ANSI guideline emphasizes identifying tasks and hazards not previously considered, particularly those associated with maintenance; and it further emphasizes teamwork among line workers, engineers, and safety professionals. The value of this critical review of concepts and methods resides in (1) its linking current risk theory to machine system risk assessment and (2) its exploration of how various risk estimation tools translate into risk-informed decisions on industrial machine system design and use. The review was undertaken to set the stage for a field evaluation study on machine risk assessment among users of the ANSI B11 TR3 method.

  11. Structure and software tools of AIDA.

    PubMed

    Duisterhout, J S; Franken, B; Witte, F

    1987-01-01

    AIDA consists of a set of software tools to allow for fast development and easy-to-maintain Medical Information Systems. AIDA supports all aspects of such a system both during development and operation. It contains tools to build and maintain forms for interactive data entry and on-line input validation, a database management system including a data dictionary and a set of run-time routines for database access, and routines for querying the database and output formatting. Unlike an application generator, the user of AIDA may select parts of the tools to fulfill his needs and program other subsystems not developed with AIDA. The AIDA software uses as host language the ANSI-standard programming language MUMPS, an interpreted language embedded in an integrated database and programming environment. This greatly facilitates the portability of AIDA applications. The database facilities supported by AIDA are based on a relational data model. This data model is built on top of the MUMPS database, the so-called global structure. This relational model overcomes the restrictions of the global structure regarding string length. The global structure is especially powerful for sorting purposes. Using MUMPS as a host language allows the user an easy interface between user-defined data validation checks or other user-defined code and the AIDA tools. AIDA has been designed primarily for prototyping and for the construction of Medical Information Systems in a research environment which requires a flexible approach. The prototyping facility of AIDA operates terminal independent and is even to a great extent multi-lingual. Most of these features are table-driven; this allows on-line changes in the use of terminal type and language, but also causes overhead. AIDA has a set of optimizing tools by which it is possible to build a faster, but (of course) less flexible code from these table definitions. By separating the AIDA software in a source and a run-time version, one is able to write

  12. Designed tools for analysis of lithography patterns and nanostructures

    NASA Astrophysics Data System (ADS)

    Dervillé, Alexandre; Baderot, Julien; Bernard, Guilhem; Foucher, Johann; Grönqvist, Hanna; Labrosse, Aurélien; Martinez, Sergio; Zimmermann, Yann

    2017-03-01

    We introduce a set of designed tools for the analysis of lithography patterns and nano structures. The classical metrological analysis of these objects has the drawbacks of being time consuming, requiring manual tuning and lacking robustness and user friendliness. With the goal of improving the current situation, we propose new image processing tools at different levels: semi automatic, automatic and machine-learning enhanced tools. The complete set of tools has been integrated into a software platform designed to transform the lab into a virtual fab. The underlying idea is to master nano processes at the research and development level by accelerating the access to knowledge and hence speed up the implementation in product lines.

  13. Effect of Thermal and Chemical Treatment on the Microstructural, Mechanical and Machining Performance of W319 Al-Si-Cu Cast Alloy Engine Blocks and Directionally Solidified Machinability Test Blocks

    NASA Astrophysics Data System (ADS)

    Szablewski, Daniel

    The research presented in this work is focused on making a link between casting microstructural, mechanical and machining properties for 319 Al-Si sand cast components. In order to achieve this, a unique Machinability Test Block (MTB) is designed to simulate the Nemak V6 Al-Si engine block solidification behavior. This MTB is then utilized to cast structures with in-situ nano-alumina particle master alloy additions that are Mg based, as well as independent in-situ Mg additions, and Sr additions to the MTB. The Universal Metallurgical Simulator and Analyzer (UMSA) Technology Platform is utilized for characterization of each cast structure at different Secondary Dendrite Arm Spacing (SDAS) levels. The rapid quench method and Jominy testing is used to assess the capability of the nano-alumina master alloy to modify the microstructure at different SDAS levels. Mechanical property assessment of the MTB is done at different SDAS levels on cast structures with master alloy additions described above. Weibull and Quality Index statistical analysis tools are then utilized to assess the mechanical properties. The MTB is also used to study single pass high speed face milling and bi-metallic cutting operations where the Al-Si hypoeutectic structure is combined with hypereutectoid Al-Si liners and cast iron cylinder liners. These studies are utilized to aid the implementation of Al-Si liners into the Nemak V6 engine block and bi-metallic cutting of the head decks. Machining behavior is also quantified for the investigated microstructures, and the Silicon Modification Level (SiML) is utilized for microstructural analysis as it relates to the machining behavior.

  14. Cyclostationarity approach for monitoring chatter and tool wear in high speed milling

    NASA Astrophysics Data System (ADS)

    Lamraoui, M.; Thomas, M.; El Badaoui, M.

    2014-02-01

    Detection of chatter and tool wear is crucial in the machining process and their monitoring is a key issue, for: (1) insuring better surface quality, (2) increasing productivity and (3) protecting both machines and safe workpiece. This paper presents an investigation of chatter and tool wear using the cyclostationary method to process the vibrations signals acquired from high speed milling. Experimental cutting tests were achieved on slot milling operation of aluminum alloy. The experimental set-up is designed for acquisition of accelerometer signals and encoding information picked up from an encoder. The encoder signal is used for re-sampling accelerometers signals in angular domain using a specific algorithm that was developed in LASPI laboratory. The use of cyclostationary on accelerometer signals has been applied for monitoring chatter and tool wear in high speed milling. The cyclostationarity appears on average properties (first order) of signals, on the energetic properties (second order) and it generates spectral lines at cyclic frequencies in spectral correlation. Angular power and kurtosis are used to analyze chatter phenomena. The formation of chatter is characterized by unstable, chaotic motion of the tool and strong anomalous fluctuations of cutting forces. Results show that stable machining generates only very few cyclostationary components of second order while chatter is strongly correlated to cyclostationary components of second order. By machining in the unstable region, chatter results in flat angular kurtosis and flat angular power, such as a pseudo (white) random signal with flat spectrum. Results reveal that spectral correlation and Wigner Ville spectrum or integrated Wigner Ville issued from second-order cyclostationary are an efficient parameter for the early diagnosis of faults in high speed machining, such as chatter, tool wear and bearings, compared to traditional stationary methods. Wigner Ville representation of the residual signal shows

  15. Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

    PubMed

    Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

    2016-01-01

    With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

  16. Quantification of uncertainty in machining operations for on-machine acceptance.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Claudet, Andre A.; Tran, Hy D.; Su, Jiann-Chemg

    2008-09-01

    Manufactured parts are designed with acceptance tolerances, i.e. deviations from ideal design conditions, due to unavoidable errors in the manufacturing process. It is necessary to measure and evaluate the manufactured part, compared to the nominal design, to determine whether the part meets design specifications. The scope of this research project is dimensional acceptance of machined parts; specifically, parts machined using numerically controlled (NC, or also CNC for Computer Numerically Controlled) machines. In the design/build/accept cycle, the designer will specify both a nominal value, and an acceptable tolerance. As part of the typical design/build/accept business practice, it is required to verifymore » that the part did meet acceptable values prior to acceptance. Manufacturing cost must include not only raw materials and added labor, but also the cost of ensuring conformance to specifications. Ensuring conformance is a substantial portion of the cost of manufacturing. In this project, the costs of measurements were approximately 50% of the cost of the machined part. In production, cost of measurement would be smaller, but still a substantial proportion of manufacturing cost. The results of this research project will point to a science-based approach to reducing the cost of ensuring conformance to specifications. The approach that we take is to determine, a priori, how well a CNC machine can manufacture a particular geometry from stock. Based on the knowledge of the manufacturing process, we are then able to decide features which need further measurements from features which can be accepted 'as is' from the CNC. By calibration of the machine tool, and establishing a machining accuracy ratio, we can validate the ability of CNC to fabricate to a particular level of tolerance. This will eliminate the costs of checking for conformance for relatively large tolerances.« less

  17. Robot based deposition of WC-Co HVOF coatings on HSS cutting tools as a substitution for solid cemented carbide cutting tools

    NASA Astrophysics Data System (ADS)

    Tillmann, W.; Schaak, C.; Biermann, D.; Aßmuth, R.; Goeke, S.

    2017-03-01

    Cemented carbide (hard metal) cutting tools are the first choice to machine hard materials or to conduct high performance cutting processes. Main advantages of cemented carbide cutting tools are their high wear resistance (hardness) and good high temperature strength. In contrast, cemented carbide cutting tools are characterized by a low toughness and generate higher production costs, especially due to limited resources. Usually, cemented carbide cutting tools are produced by means of powder metallurgical processes. Compared to conventional manufacturing routes, these processes are more expensive and only a limited number of geometries can be realized. Furthermore, post-processing and preparing the cutting edges in order to achieve high performance tools is often required. In the present paper, an alternative method to substitute solid cemented carbide cutting tools is presented. Cutting tools made of conventional high speed steels (HSS) were coated with thick WC-Co (88/12) layers by means of thermal spraying (HVOF). The challenge is to obtain a dense, homogenous, and near-net-shape coating on the flanks and the cutting edge. For this purpose, different coating strategies were realized using an industrial robot. The coating properties were subsequently investigated. After this initial step, the surfaces of the cutting tools were ground and selected cutting edges were prepared by means of wet abrasive jet machining to achieve a smooth and round micro shape. Machining tests were conducted with these coated, ground and prepared cutting tools. The occurring wear phenomena were analyzed and compared to conventional HSS cutting tools. Overall, the results of the experiments proved that the coating withstands mechanical stresses during machining. In the conducted experiments, the coated cutting tools showed less wear than conventional HSS cutting tools. With respect to the initial wear resistance, additional benefits can be obtained by preparing the cutting edge by means

  18. The Neural-fuzzy Thermal Error Compensation Controller on CNC Machining Center

    NASA Astrophysics Data System (ADS)

    Tseng, Pai-Chung; Chen, Shen-Len

    The geometric errors and structural thermal deformation are factors that influence the machining accuracy of Computer Numerical Control (CNC) machining center. Therefore, researchers pay attention to thermal error compensation technologies on CNC machine tools. Some real-time error compensation techniques have been successfully demonstrated in both laboratories and industrial sites. The compensation results still need to be enhanced. In this research, the neural-fuzzy theory has been conducted to derive a thermal prediction model. An IC-type thermometer has been used to detect the heat sources temperature variation. The thermal drifts are online measured by a touch-triggered probe with a standard bar. A thermal prediction model is then derived by neural-fuzzy theory based on the temperature variation and the thermal drifts. A Graphic User Interface (GUI) system is also built to conduct the user friendly operation interface with Insprise C++ Builder. The experimental results show that the thermal prediction model developed by neural-fuzzy theory methodology can improve machining accuracy from 80µm to 3µm. Comparison with the multi-variable linear regression analysis the compensation accuracy is increased from ±10µm to ±3µm.

  19. Machine intelligence and autonomy for aerospace systems

    NASA Technical Reports Server (NTRS)

    Heer, Ewald (Editor); Lum, Henry (Editor)

    1988-01-01

    The present volume discusses progress toward intelligent robot systems in aerospace applications, NASA Space Program automation and robotics efforts, the supervisory control of telerobotics in space, machine intelligence and crew/vehicle interfaces, expert-system terms and building tools, and knowledge-acquisition for autonomous systems. Also discussed are methods for validation of knowledge-based systems, a design methodology for knowledge-based management systems, knowledge-based simulation for aerospace systems, knowledge-based diagnosis, planning and scheduling methods in AI, the treatment of uncertainty in AI, vision-sensing techniques in aerospace applications, image-understanding techniques, tactile sensing for robots, distributed sensor integration, and the control of articulated and deformable space structures.

  20. Virtual Machine Language

    NASA Technical Reports Server (NTRS)

    Grasso, Christopher; Page, Dennis; O'Reilly, Taifun; Fteichert, Ralph; Lock, Patricia; Lin, Imin; Naviaux, Keith; Sisino, John

    2005-01-01

    Virtual Machine Language (VML) is a mission-independent, reusable software system for programming for spacecraft operations. Features of VML include a rich set of data types, named functions, parameters, IF and WHILE control structures, polymorphism, and on-the-fly creation of spacecraft commands from calculated values. Spacecraft functions can be abstracted into named blocks that reside in files aboard the spacecraft. These named blocks accept parameters and execute in a repeatable fashion. The sizes of uplink products are minimized by the ability to call blocks that implement most of the command steps. This block approach also enables some autonomous operations aboard the spacecraft, such as aerobraking, telemetry conditional monitoring, and anomaly response, without developing autonomous flight software. Operators on the ground write blocks and command sequences in a concise, high-level, human-readable programming language (also called VML ). A compiler translates the human-readable blocks and command sequences into binary files (the operations products). The flight portion of VML interprets the uplinked binary files. The ground subsystem of VML also includes an interactive sequence- execution tool hosted on workstations, which runs sequences at several thousand times real-time speed, affords debugging, and generates reports. This tool enables iterative development of blocks and sequences within times of the order of seconds.

  1. Analysis of the influence of the milling machine throw-out plate surfacing and structure design on throwing material

    NASA Astrophysics Data System (ADS)

    Fang, Yuanbin; Sha, Hongwei; Yu, Yunmin; Chen, Bing

    2018-03-01

    Material composition, hardness and wear properties of the throw-out plate improved are analysed on a road milling machine. At the same time, analyse the tissue and performance of Fe based alloy named Fe60 cladding layer using the plasma surfacing method. And the original and improved throw-out plates are analysed throwing material effect by the dynamic analysis. Then the throw-out plate samples are verified. The results show that Fe60 powder is selected as surface strengthening material. By the improved structure, the hardness of the throw-out plate increases from 14.6HRC to 57.5HRC, and the wear resistance increases from 0.452g-1 to 16.393g-1. At the same time, it increases from 3263 to 3433 to fall into the collecting material number of milling machine. It provides important guidance for structure design and process design of the milling machine throw-out plate.

  2. Teaching structure: student use of software tools for understanding macromolecular structure in an undergraduate biochemistry course.

    PubMed

    Jaswal, Sheila S; O'Hara, Patricia B; Williamson, Patrick L; Springer, Amy L

    2013-01-01

    Because understanding the structure of biological macromolecules is critical to understanding their function, students of biochemistry should become familiar not only with viewing, but also with generating and manipulating structural representations. We report a strategy from a one-semester undergraduate biochemistry course to integrate use of structural representation tools into both laboratory and homework activities. First, early in the course we introduce the use of readily available open-source software for visualizing protein structure, coincident with modules on amino acid and peptide bond properties. Second, we use these same software tools in lectures and incorporate images and other structure representations in homework tasks. Third, we require a capstone project in which teams of students examine a protein-nucleic acid complex and then use the software tools to illustrate for their classmates the salient features of the structure, relating how the structure helps explain biological function. To ensure engagement with a range of software and database features, we generated a detailed template file that can be used to explore any structure, and that guides students through specific applications of many of the software tools. In presentations, students demonstrate that they are successfully interpreting structural information, and using representations to illustrate particular points relevant to function. Thus, over the semester students integrate information about structural features of biological macromolecules into the larger discussion of the chemical basis of function. Together these assignments provide an accessible introduction to structural representation tools, allowing students to add these methods to their biochemical toolboxes early in their scientific development. © 2013 by The International Union of Biochemistry and Molecular Biology.

  3. GAPscreener: An automatic tool for screening human genetic association literature in PubMed using the support vector machine technique

    PubMed Central

    Yu, Wei; Clyne, Melinda; Dolan, Siobhan M; Yesupriya, Ajay; Wulf, Anja; Liu, Tiebin; Khoury, Muin J; Gwinn, Marta

    2008-01-01

    Background Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM), a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. Results The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. Conclusion GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge. PMID:18430222

  4. GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique.

    PubMed

    Yu, Wei; Clyne, Melinda; Dolan, Siobhan M; Yesupriya, Ajay; Wulf, Anja; Liu, Tiebin; Khoury, Muin J; Gwinn, Marta

    2008-04-22

    Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM), a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge.

  5. Using Machine Learning to Advance Personality Assessment and Theory.

    PubMed

    Bleidorn, Wiebke; Hopwood, Christopher James

    2018-05-01

    Machine learning has led to important advances in society. One of the most exciting applications of machine learning in psychological science has been the development of assessment tools that can powerfully predict human behavior and personality traits. Thus far, machine learning approaches to personality assessment have focused on the associations between social media and other digital records with established personality measures. The goal of this article is to expand the potential of machine learning approaches to personality assessment by embedding it in a more comprehensive construct validation framework. We review recent applications of machine learning to personality assessment, place machine learning research in the broader context of fundamental principles of construct validation, and provide recommendations for how to use machine learning to advance our understanding of personality.

  6. Finite Element Simulation of Machining of Ti6Al4V Alloy

    NASA Astrophysics Data System (ADS)

    Rizzuti, S.; Umbrello, D.

    2011-05-01

    Titanium and its alloys are an important class of materials, especially for aerospace applications, due to their excellent combination of strength and fracture toughness as well as low density. However, these materials are generally regarded as difficult to machine because of their low thermal conductivity and high chemical reactivity with cutting tool materials. Moreover, the low thermal conductivity of Titanium inhibits dissipation of heat within the workpiece causing an higher temperature at the cutting edge and generating for higher cutting speed a rapid chipping at the cutting edge which leads to catastrophic failure. In addition, chip morphology significantly influences the thermo-mechanical behaviour at the workpiece/tool interface, which also affects the tool life. In this paper a finite element analysis of machining of TiAl6V4 is presented. In particular, cutting force, chip morphology and segmentation are taken into account due to their predominant roles to determine machinability and tool wear during the machining of these alloys. Results in terms of residual stresses are also presented. Moreover, the numerical results are compared with experimental ones.

  7. Abnormal brain structure as a potential biomarker for venous erectile dysfunction: evidence from multimodal MRI and machine learning.

    PubMed

    Li, Lingli; Fan, Wenliang; Li, Jun; Li, Quanlin; Wang, Jin; Fan, Yang; Ye, Tianhe; Guo, Jialun; Li, Sen; Zhang, Youpeng; Cheng, Yongbiao; Tang, Yong; Zeng, Hanqing; Yang, Lian; Zhu, Zhaohui

    2018-03-29

    To investigate the cerebral structural changes related to venous erectile dysfunction (VED) and the relationship of these changes to clinical symptoms and disorder duration and distinguish patients with VED from healthy controls using a machine learning classification. 45 VED patients and 50 healthy controls were included. Voxel-based morphometry (VBM), tract-based spatial statistics (TBSS) and correlation analyses of VED patients and clinical variables were performed. The machine learning classification method was adopted to confirm its effectiveness in distinguishing VED patients from healthy controls. Compared to healthy control subjects, VED patients showed significantly decreased cortical volumes in the left postcentral gyrus and precentral gyrus, while only the right middle temporal gyrus showed a significant increase in cortical volume. Increased axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) values were observed in widespread brain regions. Certain regions of these alterations related to VED patients showed significant correlations with clinical symptoms and disorder durations. Machine learning analyses discriminated patients from controls with overall accuracy 96.7%, sensitivity 93.3% and specificity 99.0%. Cortical volume and white matter (WM) microstructural changes were observed in VED patients, and showed significant correlations with clinical symptoms and dysfunction durations. Various DTI-derived indices of some brain regions could be regarded as reliable discriminating features between VED patients and healthy control subjects, as shown by machine learning analyses. • Multimodal magnetic resonance imaging helps clinicians to assess patients with VED. • VED patients show cerebral structural alterations related to their clinical symptoms. • Machine learning analyses discriminated VED patients from controls with an excellent performance. • Machine learning classification provided a preliminary demonstration of DTI

  8. Integrated piezoelectric actuators in deep drawing tools

    NASA Astrophysics Data System (ADS)

    Neugebauer, R.; Mainda, P.; Drossel, W.-G.; Kerschner, M.; Wolf, K.

    2011-04-01

    The production of car body panels are defective in succession of process fluctuations. Thus the produced car body panel can be precise or damaged. To reduce the error rate, an intelligent deep drawing tool was developed at the Fraunhofer Institute for Machine Tools and Forming Technology IWU in cooperation with Audi and Volkswagen. Mechatronic components in a closed-loop control is the main differentiating factor between an intelligent and a conventional deep drawing tool. In correlation with sensors for process monitoring, the intelligent tool consists of piezoelectric actuators to actuate the deep drawing process. By enabling the usage of sensors and actuators at the die, the forming tool transform to a smart structure. The interface between sensors and actuators will be realized with a closed-loop control. The content of this research will present the experimental results with the piezoelectric actuator. For the analysis a production-oriented forming tool with all automotive requirements were used. The disposed actuators are monolithic multilayer actuators of the piezo injector system. In order to achieve required force, the actuators are combined in a cluster. The cluster is redundant and economical. In addition to the detailed assembly structures, this research will highlight intensive analysis with the intelligent deep drawing tool.

  9. Precision machining of advanced materials with waterjets

    NASA Astrophysics Data System (ADS)

    Liu, H. T.

    2017-01-01

    Recent advances in abrasive waterjet technology have elevated to the state that it often competes on equal footing with lasers and EDM for precision machining. Under the support of a National Science Foundation SBIR Phase II grant, OMAX has developed and commercialized micro abrasive water technology that is incorporated into a MicroMAX® JetMa- chining® Center. Waterjet technology, combined both abrasive waterjet and micro abrasive waterjet technology, is capable of machining most materials from macro to micro scales for a wide range of part size and thickness. Waterjet technology has technological and manufacturing merits that cannot be matched by most existing tools. As a cold cutting tool that creates no heat-affected zone, for example, waterjet cuts much faster than wire EDM and laser when measures to minimize a heat-affected zone are taken into account. In addition, waterjet is material independent; it cuts materials that cannot be cut or are difficult to cut otherwise. The versatility of waterjet has also demonstrated machining simulated nanomaterials with large gradients of material properties from metal, nonmetal, to anything in between. This paper presents waterjet-machined samples made of a wide range of advanced materials from macro to micro scales.

  10. Performance of machine-learning scoring functions in structure-based virtual screening.

    PubMed

    Wójcikowski, Maciej; Ballester, Pedro J; Siedlecki, Pawel

    2017-04-25

    Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and -0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary).

  11. Performance of machine-learning scoring functions in structure-based virtual screening

    PubMed Central

    Wójcikowski, Maciej; Ballester, Pedro J.; Siedlecki, Pawel

    2017-01-01

    Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and −0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary). PMID:28440302

  12. Improving Machining Accuracy of CNC Machines with Innovative Design Methods

    NASA Astrophysics Data System (ADS)

    Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

    2018-03-01

    The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

  13. Identifying the Machine Translation Error Types with the Greatest Impact on Post-editing Effort.

    PubMed

    Daems, Joke; Vandepitte, Sonia; Hartsuiker, Robert J; Macken, Lieve

    2017-01-01

    Translation Environment Tools make translators' work easier by providing them with term lists, translation memories and machine translation output. Ideally, such tools automatically predict whether it is more effortful to post-edit than to translate from scratch, and determine whether or not to provide translators with machine translation output. Current machine translation quality estimation systems heavily rely on automatic metrics, even though they do not accurately capture actual post-editing effort. In addition, these systems do not take translator experience into account, even though novices' translation processes are different from those of professional translators. In this paper, we report on the impact of machine translation errors on various types of post-editing effort indicators, for professional translators as well as student translators. We compare the impact of MT quality on a product effort indicator (HTER) with that on various process effort indicators. The translation and post-editing process of student translators and professional translators was logged with a combination of keystroke logging and eye-tracking, and the MT output was analyzed with a fine-grained translation quality assessment approach. We find that most post-editing effort indicators (product as well as process) are influenced by machine translation quality, but that different error types affect different post-editing effort indicators, confirming that a more fine-grained MT quality analysis is needed to correctly estimate actual post-editing effort. Coherence, meaning shifts, and structural issues are shown to be good indicators of post-editing effort. The additional impact of experience on these interactions between MT quality and post-editing effort is smaller than expected.

  14. Automated cell analysis tool for a genome-wide RNAi screen with support vector machine based supervised learning

    NASA Astrophysics Data System (ADS)

    Remmele, Steffen; Ritzerfeld, Julia; Nickel, Walter; Hesser, Jürgen

    2011-03-01

    RNAi-based high-throughput microscopy screens have become an important tool in biological sciences in order to decrypt mostly unknown biological functions of human genes. However, manual analysis is impossible for such screens since the amount of image data sets can often be in the hundred thousands. Reliable automated tools are thus required to analyse the fluorescence microscopy image data sets usually containing two or more reaction channels. The herein presented image analysis tool is designed to analyse an RNAi screen investigating the intracellular trafficking and targeting of acylated Src kinases. In this specific screen, a data set consists of three reaction channels and the investigated cells can appear in different phenotypes. The main issue of the image processing task is an automatic cell segmentation which has to be robust and accurate for all different phenotypes and a successive phenotype classification. The cell segmentation is done in two steps by segmenting the cell nuclei first and then using a classifier-enhanced region growing on basis of the cell nuclei to segment the cells. The classification of the cells is realized by a support vector machine which has to be trained manually using supervised learning. Furthermore, the tool is brightness invariant allowing different staining quality and it provides a quality control that copes with typical defects during preparation and acquisition. A first version of the tool has already been successfully applied for an RNAi-screen containing three hundred thousand image data sets and the SVM extended version is designed for additional screens.

  15. Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

    PubMed

    Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

    2015-01-01

    The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

  16. Dry rotary swaging with structured and coated tools

    NASA Astrophysics Data System (ADS)

    Herrmann, Marius; Schenck, Christian; Kuhfuss, Bernd

    2018-05-01

    Rotary swaging is a cold bulk forming process for manufacturing of complex bar and tube profiles like axles and gear shafts in the automotive industry. Conventional rotary swaging is carried out under intense use of lubricant usually based on mineral oil. Besides lubrication the lubricant fulfills necessary functions like lubrication, flushing and cooling, but generates costs for recycling, replacement and cleaning of the workpieces. Hence, the development of a dry process design is highly desirable, both under economic and ecological points of view. Therefore, it is necessary to substitute the functions of the lubricant. This was realized by the combination of newly developed a-C:H:W coating systems on the tools to minimize the friction and to avoid adhesion effects. With the application of a deterministic structure in the forging zone of the tools the friction conditions are modified to control the axial process forces. In this study infeed rotary swaging with functionalized tools was experimentally investigated. Therefore, steel and aluminum tubes were formed with and without lubricant. Different structures which were coated and uncoated were implemented in the reduction zone of the tools. The antagonistic effects of coating and structuring were characterized by measuring the axial process force and the produced workpiece quality in terms of roundness and surface roughness. Thus, the presented results allow for further developments towards a dry rotary swaging process.

  17. Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

    PubMed

    Jongin Kim; Boreom Lee

    2017-07-01

    The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

  18. Machine learning molecular dynamics for the simulation of infrared spectra.

    PubMed

    Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

    2017-10-01

    Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

  19. Chapter 9: The FTU Machine - Design Construction and Assembly

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pizzuto, A.; Annino, C.; Baldarelli, M.

    2004-05-15

    The main design features and guidelines for the construction of the 8-T cryogenically cooled Frascati Tokamak Upgrade (FTU) are presented. The main features include the very compact toroidal magnets based on the concept of the 'Bitter' type of coil with wedge-shaped turns, utilized for the first time for the Alcator A and C magnets, and the original configuration of the vacuum vessel (VV) structure, which is fully welded in order to achieve the required high strength and electric resistivity. The present toroidal limiter has been installed following several years of operation, and this installation has required the development of specificmore » remote-handling tools. The toroidal limiter consists of 12 independent sectors made of stainless steel carriers and molybdenum alloy (TZM) tiles. The main fabrication processes developed for the toroidal and poloidal coils as well as for the VV are described. It is to be noted that the assembly procedure has required very accurate machining of all the structures requiring several trials and steps. The machine has shown no problem in operating routinely at its maximum design values (8 T, 1.6 MA)« less

  20. Fabrication of locally micro-structured fiber Bragg gratings by fs-laser machining

    NASA Astrophysics Data System (ADS)

    Dutz, Franz J.; Stephan, Valentin; Marchi, Gabriele; Koch, Alexander W.; Roths, Johannes; Huber, Heinz P.

    2018-06-01

    Here, we describe a method for producing locally micro-structured fiber Bragg gratings (LMFGB) by fs-laser machining. This technique enables the precise and reproducible ablation of cladding material to create circumferential grooves inside the claddings of optical fibers. From initial ablation experiments we acquired optimized process parameters. The fabricated grooves were located in the middle of uniform type I fiber Bragg gratings. LMFBGs with four different groove widths of 48, 85, 135 and 205 μ { {m}} were produced. The grooves exhibited constant depths of about 30 μ {m} and steep sidewall angles. With the combination of micro-structures and fiber Bragg gratings, fiber optic sensor elements with enhanced functionalities can be achieved.

  1. Tool Wear Monitoring Using Time Series Analysis

    NASA Astrophysics Data System (ADS)

    Song, Dong Yeul; Ohara, Yasuhiro; Tamaki, Haruo; Suga, Masanobu

    A tool wear monitoring approach considering the nonlinear behavior of cutting mechanism caused by tool wear and/or localized chipping is proposed, and its effectiveness is verified through the cutting experiment and actual turning machining. Moreover, the variation in the surface roughness of the machined workpiece is also discussed using this approach. In this approach, the residual error between the actually measured vibration signal and the estimated signal obtained from the time series model corresponding to dynamic model of cutting is introduced as the feature of diagnosis. Consequently, it is found that the early tool wear state (i.e. flank wear under 40µm) can be monitored, and also the optimal tool exchange time and the tool wear state for actual turning machining can be judged by this change in the residual error. Moreover, the variation of surface roughness Pz in the range of 3 to 8µm can be estimated by the monitoring of the residual error.

  2. Tools and procedures for visualization of proteins and other biomolecules.

    PubMed

    Pan, Lurong; Aller, Stephen G

    2015-04-01

    Protein, peptides, and nucleic acids are biomolecules that drive biological processes in living organisms. An enormous amount of structural data for a large number of these biomolecules has been described with atomic precision in the form of structural "snapshots" that are freely available in public repositories. These snapshots can help explain how the biomolecules function, the nature of interactions between multi-molecular complexes, and even how small-molecule drugs can modulate the biomolecules for clinical benefits. Furthermore, these structural snapshots serve as inputs for sophisticated computer simulations to turn the biomolecules into moving, "breathing" molecular machines for understanding their dynamic properties in real-time computer simulations. In order for the researcher to take advantage of such a wealth of structural data, it is necessary to gain competency in the use of computer molecular visualization tools for exploring the structures and visualizing three-dimensional spatial representations. Here, we present protocols for using two common visualization tools--the Web-based Jmol and the stand-alone PyMOL package--as well as a few examples of other popular tools. Copyright © 2015 John Wiley & Sons, Inc.

  3. A Turing Machine Simulator.

    ERIC Educational Resources Information Center

    Navarro, Aaron B.

    1981-01-01

    Presents a program in Level II BASIC for a TRS-80 computer that simulates a Turing machine and discusses the nature of the device. The program is run interactively and is designed to be used as an educational tool by computer science or mathematics students studying computational or automata theory. (MP)

  4. Machine Learning for Medical Imaging

    PubMed Central

    Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L.

    2017-01-01

    Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. ©RSNA, 2017 PMID:28212054

  5. Machine Learning for Medical Imaging.

    PubMed

    Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

    2017-01-01

    Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

  6. Using machine learning to identify structural breaks in single-group interrupted time series designs.

    PubMed

    Linden, Ariel; Yarnold, Paul R

    2016-12-01

    Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the intervention is expected to 'interrupt' the level and/or trend of the time series, subsequent to its introduction. Given that the internal validity of the design rests on the premise that the interruption in the time series is associated with the introduction of the treatment, treatment effects may seem less plausible if a parallel trend already exists in the time series prior to the actual intervention. Thus, sensitivity analyses should focus on detecting structural breaks in the time series before the intervention. In this paper, we introduce a machine-learning algorithm called optimal discriminant analysis (ODA) as an approach to determine if structural breaks can be identified in years prior to the initiation of the intervention, using data from California's 1988 voter-initiated Proposition 99 to reduce smoking rates. The ODA analysis indicates that numerous structural breaks occurred prior to the actual initiation of Proposition 99 in 1989, including perfect structural breaks in 1983 and 1985, thereby casting doubt on the validity of treatment effects estimated for the actual intervention when using a single-group ITSA design. Given the widespread use of ITSA for evaluating observational data and the increasing use of machine-learning techniques in traditional research, we recommend that structural break sensitivity analysis is routinely incorporated in all research using the single-group ITSA design. © 2016 John Wiley & Sons, Ltd.

  7. Pocket-sized versus standard ultrasound machines in abdominal imaging.

    PubMed

    Tse, K H; Luk, W H; Lam, M C

    2014-06-01

    The pocket-sized ultrasound machine has emerged as an invaluable tool for quick assessment in emergency and general practice settings. It is suitable for instant and quick assessment in cardiac imaging. However, its applicability in the imaging of other body parts has yet to be established. In this pictorial review, we compared the performance of the pocketsized ultrasound machine against the standard ultrasound machine for its image quality in common abdominal pathology.

  8. GeneMachine: gene prediction and sequence annotation.

    PubMed

    Makalowska, I; Ryan, J F; Baxevanis, A D

    2001-09-01

    A number of free-standing programs have been developed in order to help researchers find potential coding regions and deduce gene structure for long stretches of what is essentially 'anonymous DNA'. As these programs apply inherently different criteria to the question of what is and is not a coding region, multiple algorithms should be used in the course of positional cloning and positional candidate projects to assure that all potential coding regions within a previously-identified critical region are identified. We have developed a gene identification tool called GeneMachine which allows users to query multiple exon and gene prediction programs in an automated fashion. BLAST searches are also performed in order to see whether a previously-characterized coding region corresponds to a region in the query sequence. A suite of Perl programs and modules are used to run MZEF, GENSCAN, GRAIL 2, FGENES, RepeatMasker, Sputnik, and BLAST. The results of these runs are then parsed and written into ASN.1 format. Output files can be opened using NCBI Sequin, in essence using Sequin as both a workbench and as a graphical viewer. The main feature of GeneMachine is that the process is fully automated; the user is only required to launch GeneMachine and then open the resulting file with Sequin. Annotations can then be made to these results prior to submission to GenBank, thereby increasing the intrinsic value of these data. GeneMachine is freely-available for download at http://genome.nhgri.nih.gov/genemachine. A public Web interface to the GeneMachine server for academic and not-for-profit users is available at http://genemachine.nhgri.nih.gov. The Web supplement to this paper may be found at http://genome.nhgri.nih.gov/genemachine/supplement/.

  9. FINDSITE-metal: Integrating evolutionary information and machine learning for structure-based metal binding site prediction at the proteome level

    PubMed Central

    Brylinski, Michal; Skolnick, Jeffrey

    2010-01-01

    The rapid accumulation of gene sequences, many of which are hypothetical proteins with unknown function, has stimulated the development of accurate computational tools for protein function prediction with evolution/structure-based approaches showing considerable promise. In this paper, we present FINDSITE-metal, a new threading-based method designed specifically to detect metal binding sites in modeled protein structures. Comprehensive benchmarks using different quality protein structures show that weakly homologous protein models provide sufficient structural information for quite accurate annotation by FINDSITE-metal. Combining structure/evolutionary information with machine learning results in highly accurate metal binding annotations; for protein models constructed by TASSER, whose average Cα RMSD from the native structure is 8.9 Å, 59.5% (71.9%) of the best of top five predicted metal locations are within 4 Å (8 Å) from a bound metal in the crystal structure. For most of the targets, multiple metal binding sites are detected with the best predicted binding site at rank 1 and within the top 2 ranks in 65.6% and 83.1% of the cases, respectively. Furthermore, for iron, copper, zinc, calcium and magnesium ions, the binding metal can be predicted with high, typically 70-90%, accuracy. FINDSITE-metal also provides a set of confidence indexes that help assess the reliability of predictions. Finally, we describe the proteome-wide application of FINDSITE-metal that quantifies the metal binding complement of the human proteome. FINDSITE-metal is freely available to the academic community at http://cssb.biology.gatech.edu/findsite-metal/. PMID:21287609

  10. Self-Calibrating Surface Measuring Machine

    NASA Astrophysics Data System (ADS)

    Greenleaf, Allen H.

    1983-04-01

    A new kind of surface-measuring machine has been developed under government contract at Itek Optical Systems, a Division of Itek Corporation, to assist in the fabrication of large, highly aspheric optical elements. The machine uses four steerable distance-measuring interferometers at the corners of a tetrahedron to measure the positions of a retroreflective target placed at various locations against the surface being measured. Using four interferometers gives redundant information so that, from a set of measurement data, the dimensions of the machine as well as the coordinates of the measurement points can be determined. The machine is, therefore, self-calibrating and does not require a structure made to high accuracy. A wood-structured prototype of this machine was made whose key components are a simple form of air bearing steering mirror, a wide-angle cat's eye retroreflector used as the movable target, and tracking sensors and servos to provide automatic tracking of the cat's eye by the four laser beams. The data are taken and analyzed by computer. The output is given in terms of error relative to an equation of the desired surface. In tests of this machine, measurements of a 0.7 m diameter mirror blank have been made with an accuracy on the order of 0.2µm rms.

  11. Monitoring machining conditions by infrared images

    NASA Astrophysics Data System (ADS)

    Borelli, Joao E.; Gonzaga Trabasso, Luis; Gonzaga, Adilson; Coelho, Reginaldo T.

    2001-03-01

    During machining process the knowledge of the temperature is the most important factor in tool analysis. It allows to control main factors that influence tool use, life time and waste. The temperature in the contact area between the piece and the tool is resulting from the material removal in cutting operation and it is too difficult to be obtained because the tool and the work piece are in motion. One way to measure the temperature in this situation is detecting the infrared radiation. This work presents a new methodology for diagnosis and monitoring of machining processes with the use of infrared images. The infrared image provides a map in gray tones of the elements in the process: tool, work piece and chips. Each gray tone in the image corresponds to a certain temperature for each one of those materials and the relationship between the gray tones and the temperature is gotten by the previous of infrared camera calibration. The system developed in this work uses an infrared camera, a frame grabber board and a software composed of three modules. The first module makes the image acquisition and processing. The second module makes the feature image extraction and performs the feature vector. Finally, the third module uses fuzzy logic to evaluate the feature vector and supplies the tool state diagnostic as output.

  12. Identifying product order with restricted Boltzmann machines

    NASA Astrophysics Data System (ADS)

    Rao, Wen-Jia; Li, Zhenyu; Zhu, Qiong; Luo, Mingxing; Wan, Xin

    2018-03-01

    Unsupervised machine learning via a restricted Boltzmann machine is a useful tool in distinguishing an ordered phase from a disordered phase. Here we study its application on the two-dimensional Ashkin-Teller model, which features a partially ordered product phase. We train the neural network with spin configuration data generated by Monte Carlo simulations and show that distinct features of the product phase can be learned from nonergodic samples resulting from symmetry breaking. Careful analysis of the weight matrices inspires us to define a nontrivial machine-learning motivated quantity of the product form, which resembles the conventional product order parameter.

  13. Nonlinear Shaping Architecture Designed with Using Evolutionary Structural Optimization Tools

    NASA Astrophysics Data System (ADS)

    Januszkiewicz, Krystyna; Banachowicz, Marta

    2017-10-01

    The paper explores the possibilities of using Structural Optimization Tools (ESO) digital tools in an integrated structural and architectural design in response to the current needs geared towards sustainability, combining ecological and economic efficiency. The first part of the paper defines the Evolutionary Structural Optimization tools, which were developed specifically for engineering purposes using finite element analysis as a framework. The development of ESO has led to several incarnations, which are all briefly discussed (Additive ESO, Bi-directional ESO, Extended ESO). The second part presents result of using these tools in structural and architectural design. Actual building projects which involve optimization as a part of the original design process will be presented (Crematorium in Kakamigahara Gifu, Japan, 2006 SANAA“s Learning Centre, EPFL in Lausanne, Switzerland 2008 among others). The conclusion emphasizes that the structural engineering and architectural design mean directing attention to the solutions which are used by Nature, designing works optimally shaped and forming their own environments. Architectural forms never constitute the optimum shape derived through a form-finding process driven only by structural optimization, but rather embody and integrate a multitude of parameters. It might be assumed that there is a similarity between these processes in nature and the presented design methods. Contemporary digital methods make the simulation of such processes possible, and thus enable us to refer back to the empirical methods of previous generations.

  14. Simulation tools for guided wave based structural health monitoring

    NASA Astrophysics Data System (ADS)

    Mesnil, Olivier; Imperiale, Alexandre; Demaldent, Edouard; Baronian, Vahan; Chapuis, Bastien

    2018-04-01

    Structural Health Monitoring (SHM) is a thematic derived from Non Destructive Evaluation (NDE) based on the integration of sensors onto or into a structure in order to monitor its health without disturbing its regular operating cycle. Guided wave based SHM relies on the propagation of guided waves in plate-like or extruded structures. Using piezoelectric transducers to generate and receive guided waves is one of the most widely accepted paradigms due to the low cost and low weight of those sensors. A wide range of techniques for flaw detection based on the aforementioned setup is available in the literature but very few of these techniques have found industrial applications yet. A major difficulty comes from the sensitivity of guided waves to a substantial number of parameters such as the temperature or geometrical singularities, making guided wave measurement difficult to analyze. In order to apply guided wave based SHM techniques to a wider spectrum of applications and to transfer those techniques to the industry, the CEA LIST develops novel numerical methods. These methods facilitate the evaluation of the robustness of SHM techniques for multiple applicative cases and ease the analysis of the influence of various parameters, such as sensors positioning or environmental conditions. The first numerical tool is the guided wave module integrated to the commercial software CIVA, relying on a hybrid modal-finite element formulation to compute the guided wave response of perturbations (cavities, flaws…) in extruded structures of arbitrary cross section such as rails or pipes. The second numerical tool is based on the spectral element method [2] and simulates guided waves in both isotropic (metals) and orthotropic (composites) plate like-structures. This tool is designed to match the widely accepted sparse piezoelectric transducer array SHM configuration in which each embedded sensor acts as both emitter and receiver of guided waves. This tool is under development and

  15. Implementation of machine learning for high-volume manufacturing metrology challenges (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Timoney, Padraig; Kagalwala, Taher; Reis, Edward; Lazkani, Houssam; Hurley, Jonathan; Liu, Haibo; Kang, Charles; Isbester, Paul; Yellai, Naren; Shifrin, Michael; Etzioni, Yoav

    2018-03-01

    In recent years, the combination of device scaling, complex 3D device architecture and tightening process tolerances have strained the capabilities of optical metrology tools to meet process needs. Two main categories of approaches have been taken to address the evolving process needs. In the first category, new hardware configurations are developed to provide more spectral sensitivity. Most of this category of work will enable next generation optical metrology tools to try to maintain pace with next generation process needs. In the second category, new innovative algorithms have been pursued to increase the value of the existing measurement signal. These algorithms aim to boost sensitivity to the measurement parameter of interest, while reducing the impact of other factors that contribute to signal variability but are not influenced by the process of interest. This paper will evaluate the suitability of machine learning to address high volume manufacturing metrology requirements in both front end of line (FEOL) and back end of line (BEOL) sectors from advanced technology nodes. In the FEOL sector, initial feasibility has been demonstrated to predict the fin CD values from an inline measurement using machine learning. In this study, OCD spectra were acquired after an etch process that occurs earlier in the process flow than where the inline CD is measured. The fin hard mask etch process is known to impact the downstream inline CD value. Figure 1 shows the correlation of predicted CD vs downstream inline CD measurement obtained after the training of the machine learning algorithm. For BEOL, machine learning is shown to provide an additional source of information in prediction of electrical resistance from structures that are not compatible for direct copper height measurement. Figure 2 compares the trench height correlation to electrical resistance (Rs) and the correlation of predicted Rs to the e-test Rs value for a far back end of line (FBEOL) metallization level

  16. Testing Machine for Biaxial Loading

    NASA Technical Reports Server (NTRS)

    Demonet, R. J.; Reeves, R. D.

    1985-01-01

    Standard tensile-testing machine applies bending and tension simultaneously. Biaxial-loading test machine created by adding two test fixtures to commercial tensile-testing machine. Bending moment applied by substrate-deformation fixture comprising yoke and anvil block. Pneumatic tension-load fixture pulls up on bracket attached to top surface of specimen. Tension and deflection measured with transducers. Modified test apparatus originally developed to load-test Space Shuttle surface-insulation tiles and particuarly important for composite structures.

  17. Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles

    DOE PAGES

    Timoshenko, Janis; Lu, Deyu; Lin, Yuewei; ...

    2017-09-29

    Tracking the structure of heterogeneous catalysts under operando conditions remains a challenge due to the paucity of experimental techniques that can provide atomic-level information for catalytic metal species. Here we report on the use of X-ray absorption near edge structure (XANES) spectroscopy and supervised machine learning (SML) for refining the three-dimensional geometry of metal catalysts. SML is used to unravel the hidden relationship between the XANES features and catalyst geometry. To train our SML method, we rely on ab-initio XANES simulations. Our approach allows one to solve the structure of a metal catalyst from its experimental XANES, as demonstrated heremore » by reconstructing the average size, shape and morphology of well-defined platinum nanoparticles. This method is applicable to the determination of the nanoparticle structure in operando studies and can be generalized to other nanoscale systems. In conclusion, it also allows on-the-fly XANES analysis, and is a promising approach for high-throughput and time-dependent studies.« less

  18. Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Timoshenko, Janis; Lu, Deyu; Lin, Yuewei

    Tracking the structure of heterogeneous catalysts under operando conditions remains a challenge due to the paucity of experimental techniques that can provide atomic-level information for catalytic metal species. Here we report on the use of X-ray absorption near edge structure (XANES) spectroscopy and supervised machine learning (SML) for refining the three-dimensional geometry of metal catalysts. SML is used to unravel the hidden relationship between the XANES features and catalyst geometry. To train our SML method, we rely on ab-initio XANES simulations. Our approach allows one to solve the structure of a metal catalyst from its experimental XANES, as demonstrated heremore » by reconstructing the average size, shape and morphology of well-defined platinum nanoparticles. This method is applicable to the determination of the nanoparticle structure in operando studies and can be generalized to other nanoscale systems. In conclusion, it also allows on-the-fly XANES analysis, and is a promising approach for high-throughput and time-dependent studies.« less

  19. 41 CFR 50-204.5 - Machine guarding.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... usually require point of operation guarding: Guillotine cutters. Shears. Alligator shears. Power presses. Milling machines. Power saws. Jointers. Portable power tools. Forming rolls and calenders. (d) Revolving...

  20. [Design of Complex Cavity Structure in Air Route System of Automated Peritoneal Dialysis Machine].

    PubMed

    Quan, Xiaoliang

    2017-07-30

    This paper introduced problems about Automated Peritoneal Dialysis machine(APD) that the lack of technical issues such as the structural design of the complex cavities. To study the flow characteristics of this special structure, the application of ANSYS CFX software is used with k-ε turbulence model as the theoretical basis of fluid mechanics. The numerical simulation of flow field simulation result in the internal model can be gotten after the complex structure model is imported into ANSYS CFX module. Then, it will present the distribution of complex cavities inside the flow field and the flow characteristics parameter, which will provide an important reference design for APD design.