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…

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…

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…

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…

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…

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).…

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.

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

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

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…

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…

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…

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…

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…

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…

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…

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.

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.

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…

High speed turning of compacted graphite iron using controlled modulation

NASA Astrophysics Data System (ADS)

Stalbaum, Tyler Paul

Compacted graphite iron (CGI) is a material which emerged as a candidate material to replace cast iron (CI) in the automotive industry for engine block castings. Its thermal and mechanical properties allow the CGI-based engines to operate at higher cylinder pressures and temperatures than CI-based engines, allowing for lower fuel emissions and increased fuel economy. However, these same properties together with the thermomechanical wear mode in the CGI-CBN system result in poor machinability and inhibit CGI from seeing wide spread use in the automotive industry. In industry, machining of CGI is done only at low speeds, less than V = 200 m/min, to avoid encountering rapid wear of the cutting tools during cutting. Studies have suggested intermittent cutting operations such as milling suffer less severe tool wear than continuous cutting. Furthermore, evidence that a hard sulfide layer which forms over the cutting edge in machining CI at high speeds is absent during machining CGI is a major factor in the difference in machinability of these material systems. The present study addresses both of these issues by modification to the conventional machining process to allow intermittent continuous cutting. The application of controlled modulation superimposed onto the cutting process -- modulation-assisted machining (MAM) -- is shown to be quite effective in reducing the wear of cubic boron nitride (CBN) tools when machining CGI at high machining speeds (> 500 m/min). The tool life is at least 20 times greater than found in conventional machining of CGI. This significant reduction in wear is a consequence of reduction in the severity of the tool-work contact conditions with MAM. The propensity for thermochemical wear of CBN is thus reduced. It is found that higher cutting speed (> 700 m/min) leads to lower tool wear with MAM. The MAM configuration employing feed-direction modulation appears feasible for implementation at high speeds and offers a solution to this challenging class of industrial machining applications. This study's approach is by series of high speed turning tests of CGI with CBN tools, comparing conventional machining to MAM for similar parameters otherwise, by tool wear measurements and machinability observations.

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.

“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

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.

Detection of Cutting Tool Wear using Statistical Analysis and Regression Model

NASA Astrophysics Data System (ADS)

Ghani, Jaharah A.; Rizal, Muhammad; Nuawi, Mohd Zaki; Haron, Che Hassan Che; Ramli, Rizauddin

2010-10-01

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

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.…

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.

Measurement of W + bb and a search for MSSM Higgs bosons with the CMS detector at the LHC

NASA Astrophysics Data System (ADS)

O'Connor, Alexander Pinpin

Tooling used to cure composite laminates in the aerospace and automotive industries must provide a dimensionally stable geometry throughout the thermal cycle applied during the part curing process. This requires that the Coefficient of Thermal Expansion (CTE) of the tooling materials match that of the composite being cured. The traditional tooling material for production applications is a nickel alloy. Poor machinability and high material costs increase the expense of metallic tooling made from nickel alloys such as 'Invar 36' or 'Invar 42'. Currently, metallic tooling is unable to meet the needs of applications requiring rapid affordable tooling solutions. In applications where the tooling is not required to have the durability provided by metals, such as for small area repair, an opportunity exists for non-metallic tooling materials like graphite, carbon foams, composites, or ceramics and machinable glasses. Nevertheless, efficient machining of brittle, non-metallic materials is challenging due to low ductility, porosity, and high hardness. The machining of a layup tool comprises a large portion of the final cost. Achieving maximum process economy requires optimization of the machining process in the given tooling material. Therefore, machinability of the tooling material is a critical aspect of the overall cost of the tool. In this work, three commercially available, brittle/porous, non-metallic candidate tooling materials were selected, namely: (AAC) Autoclaved Aerated Concrete, CB1100 ceramic block and Cfoam carbon foam. Machining tests were conducted in order to evaluate the machinability of these materials using end milling. Chip formation, cutting forces, cutting tool wear, machining induced damage, surface quality and surface integrity were investigated using High Speed Steel (HSS), carbide, diamond abrasive and Polycrystalline Diamond (PCD) cutting tools. Cutting forces were found to be random in magnitude, which was a result of material porosity. The abrasive nature of Cfoam produced rapid tool wear when using HSS and PCD type cutting tools. However, tool wear was not significant in AAC or CB1100 regardless of the type of cutting edge. Machining induced damage was observed in the form of macro-scale chipping and fracture in combination with micro-scale cracking. Transverse rupture test results revealed significant reductions in residual strength and damage tolerance in CB1100. In contrast, AAC and Cfoam showed no correlation between machining induced damage and a reduction in surface integrity. Cutting forces in machining were modeled for all materials. Cutting force regression models were developed based on Design of Experiment and Analysis of Variance. A mechanistic cutting force model was proposed based upon conventional end milling force models and statistical distributions of material porosity. In order to validate the model, predicted cutting forces were compared to experimental results. Predicted cutting forces agreed well with experimental measurements. Furthermore, over the range of cutting conditions tested, the proposed model was shown to have comparable predictive accuracy to empirically produced regression models; greatly reducing the number of cutting tests required to simulate cutting forces. Further, this work demonstrates a key adaptation of metallic cutting force models to brittle porous material; a vital step in the research into the machining of these materials using end milling.

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.

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

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.

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.

minimega

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

David Fritz, John Floren

2013-08-27

Minimega is a simple emulytics platform for creating testbeds of networked devices. The platform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. Minimega attempts to allow experiments to be brought up quickly with nearly no configuration. Minimega also includes tools for simple cluster management, as well as tools for creating Linux based virtual machine images.

Howitzer Ammunition System Procurement (HASP).

DTIC Science & Technology

1991-07-01

machine tools , etc.) * Most critical part of base to reassemble. IPP * Industry to plan round-specific...beyond allowed tolerances. - Conducting tolerance studies and funding machining studies at sul’on "’actors. " Facility development was controlled by the...Manufacturing Balimoy Mfg. of Venice, Inc. Action Manufacturing Co. Lanson Industries Inc. Hercules Aerospace Company CIMA Machine & Tool Co., Inc. Talley Defense Systems Tracor Aerospace Inc. BMY E49030APPBMAC

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.

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.

Diamond Turning Of Infra-Red Components

NASA Astrophysics Data System (ADS)

Hodgson, B.; Lettington, A. H.; Stillwell, P. F. T. C.

1986-05-01

Single point diamond machining of infra-red optical components such as aluminium mirrors, germanium lenses and zinc sulphide domes is potentially the most cost effective method for their manufacture since components may be machined from the blanks to a high surface finish, requiring no subsequent polishing, in a few minutes. Machines for the production of flat surfaces are well established. Diamond turning lathes for curved surfaces however require a high capital investment which can be justified only for research purposes or high volume production. The present paper describes the development of a low cost production machine based on a Bryant Symons diamond turning lathe which is able to machine spherical components to the required form and finish. It employs two horizontal spindles one for the workpiece the other for the tool. The machined radius of curvature is set by the alignment of the axes and the radius of the tool motion, as in conventional generation. The diamond tool is always normal to the workpiece and does not need to be accurately profiled. There are two variants of this basic machine. For machining hemispherical domes the axes are at right angles while for lenses with positive or negative curvature these axes are adjustable. An aspherical machine is under development, based on the all mechanical spherical machine, but in which a ± 2 mm aspherecity may be imposed on the best fit sphere by moving the work spindle under numerical control.

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

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.

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.

Osteoporosis risk prediction for bone mineral density assessment of postmenopausal women using machine learning.

PubMed

Yoo, Tae Keun; Kim, Sung Kean; Kim, Deok Won; Choi, Joon Yul; Lee, Wan Hyung; Oh, Ein; Park, Eun-Cheol

2013-11-01

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 compared to the ability of conventional clinical decision tools. We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Examination Surveys. The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests, artificial neural networks (ANN), and logistic regression (LR) based on simple surveys. The machine learning models were compared to four conventional clinical decision tools: osteoporosis self-assessment tool (OST), osteoporosis risk assessment instrument (ORAI), simple calculated osteoporosis risk estimation (SCORE), and osteoporosis index of risk (OSIRIS). SVM had significantly better area under the curve (AUC) of the receiver operating characteristic than ANN, LR, OST, ORAI, SCORE, and OSIRIS for the training set. SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0% at total hip, femoral neck, or lumbar spine for the testing set. The significant factors selected by SVM were age, height, weight, body mass index, duration of menopause, duration of breast feeding, estrogen therapy, hyperlipidemia, hypertension, osteoarthritis, and diabetes mellitus. Considering various predictors associated with low bone density, the machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

Open architecture CNC system

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

Tal, J.; Lopez, A.; Edwards, J.M.

1995-04-01

In this paper, an alternative solution to the traditional CNC machine tool controller has been introduced. Software and hardware modules have been described and their incorporation in a CNC control system has been outlined. This type of CNC machine tool controller demonstrates that technology is accessible and can be readily implemented into an open architecture machine tool controller. Benefit to the user is greater controller flexibility, while being economically achievable. PC based, motion as well as non-motion features will provide flexibility through a Windows environment. Up-grading this type of controller system through software revisions will keep the machine tool inmore » a competitive state with minimal effort. Software and hardware modules are mass produced permitting competitive procurement and incorporation. Open architecture CNC systems provide diagnostics thus enhancing maintainability, and machine tool up-time. A major concern of traditional CNC systems has been operator training time. Training time can be greatly minimized by making use of Windows environment features.« less

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.

Influence of non-edible vegetable based oil as cutting fluid on chip, surface roughness and cutting force during drilling operation of Mild Steel

NASA Astrophysics Data System (ADS)

Susmitha, M.; Sharan, P.; Jyothi, P. N.

2016-09-01

Friction between work piece-cutting tool-chip generates heat in the machining zone. The heat generated reduces the tool life, increases surface roughness and decreases the dimensional sensitiveness of work material. This can be overcome by using cutting fluids during machining. They are used to provide lubrication and cooling effects between cutting tool and work piece and cutting tool and chip during machining operation. As a result, important benefits would be achieved such longer tool life, easy chip flow and higher machining quality in the machining processes. Non-edible vegetable oils have received considerable research attention in the last decades owing to their remarkable improved tribological characteristics and due to increasing attention to environmental issues, have driven the lubricant industry toward eco friendly products from renewable sources. In the present work, different non-edible vegetable oils are used as cutting fluid during drilling of Mild steel work piece. Non-edible vegetable oils, used are Karanja oil (Honge), Neem oil and blend of these two oils. The effect of these cutting fluids on chip formation, surface roughness and cutting force are investigated and the results obtained are compared with results obtained with petroleum based cutting fluids and dry conditions.

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.

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

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.

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.

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.

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.

Machine learning-based methods for prediction of linear B-cell epitopes.

PubMed

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

A probabilistic-based approach to monitoring tool wear state and assessing its effect on workpiece quality in nickel-based alloys

NASA Astrophysics Data System (ADS)

Akhavan Niaki, Farbod

The objective of this research is first to investigate the applicability and advantage of statistical state estimation methods for predicting tool wear in machining nickel-based superalloys over deterministic methods, and second to study the effects of cutting tool wear on the quality of the part. Nickel-based superalloys are among those classes of materials that are known as hard-to-machine alloys. These materials exhibit a unique combination of maintaining their strength at high temperature and have high resistance to corrosion and creep. These unique characteristics make them an ideal candidate for harsh environments like combustion chambers of gas turbines. However, the same characteristics that make nickel-based alloys suitable for aggressive conditions introduce difficulties when machining them. High strength and low thermal conductivity accelerate the cutting tool wear and increase the possibility of the in-process tool breakage. A blunt tool nominally deteriorates the surface integrity and damages quality of the machined part by inducing high tensile residual stresses, generating micro-cracks, altering the microstructure or leaving a poor roughness profile behind. As a consequence in this case, the expensive superalloy would have to be scrapped. The current dominant solution for industry is to sacrifice the productivity rate by replacing the tool in the early stages of its life or to choose conservative cutting conditions in order to lower the wear rate and preserve workpiece quality. Thus, monitoring the state of the cutting tool and estimating its effects on part quality is a critical task for increasing productivity and profitability in machining superalloys. This work aims to first introduce a probabilistic-based framework for estimating tool wear in milling and turning of superalloys and second to study the detrimental effects of functional state of the cutting tool in terms of wear and wear rate on part quality. In the milling operation, the mechanisms of tool failure were first identified and, based on the rapid catastrophic failure of the tool, a Bayesian inference method (i.e., Markov Chain Monte Carlo, MCMC) was used for parameter calibration of tool wear using a power mechanistic model. The calibrated model was then used in the state space probabilistic framework of a Kalman filter to estimate the tool flank wear. Furthermore, an on-machine laser measuring system was utilized and fused into the Kalman filter to improve the estimation accuracy. In the turning operation the behavior of progressive wear was investigated as well. Due to the nonlinear nature of wear in turning, an extended Kalman filter was designed for tracking progressive wear, and the results of the probabilistic-based method were compared with a deterministic technique, where significant improvement (more than 60% increase in estimation accuracy) was achieved. To fulfill the second objective of this research in understanding the underlying effects of wear on part quality in cutting nickel-based superalloys, a comprehensive study on surface roughness, dimensional integrity and residual stress was conducted. The estimated results derived from a probabilistic filter were used for finding the proper correlations between wear, surface roughness and dimensional integrity, along with a finite element simulation for predicting the residual stress profile for sharp and worn cutting tool conditions. The output of this research provides the essential information on condition monitoring of the tool and its effects on product quality. The low-cost Hall effect sensor used in this work to capture spindle power in the context of the stochastic filter can effectively estimate tool wear in both milling and turning operations, while the estimated wear can be used to generate knowledge of the state of workpiece surface integrity. Therefore the true functionality and efficiency of the tool in superalloy machining can be evaluated without additional high-cost sensing.

Design of robotic cells based on relative handling modules with use of SolidWorks system

NASA Astrophysics Data System (ADS)

Gaponenko, E. V.; Anciferov, S. I.

2018-05-01

The article presents a diagramed engineering solution for a robotic cell with six degrees of freedom for machining of complex details, consisting of the base with a tool installation module and a detail machining module made as parallel structure mechanisms. The output links of the detail machining module and the tool installation module can move along X-Y-Z coordinate axes each. A 3D-model of the complex is designed in the SolidWorks system. It will be used further for carrying out engineering calculations and mathematical analysis and obtaining all required documentation.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

PubMed

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining

PubMed Central

Salehi, Mojtaba

2010-01-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously. PMID:21845020

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.

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.

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.

A Study on Micro-Machining Technology for the Machining of NiTi: Five-Axis Micro-Milling and Micro Deep-Hole Drilling

NASA Astrophysics Data System (ADS)

Biermann, D.; Kahleyss, F.; Krebs, E.; Upmeier, T.

2011-07-01

Micro-sized applications are gaining more and more relevance for NiTi-based shape memory alloys (SMA). Different types of micro-machining offer unique possibilities for the manufacturing of NiTi components. The advantage of machining is the low thermal influence on the workpiece. This is important, because the phase transformation temperatures of NiTi SMAs can be changed and the components may need extensive post manufacturing. The article offers a simulation-based approach to optimize five-axis micro-milling processes with respect to the special material properties of NiTi SMA. Especially, the influence of the various tool inclination angles is considered for introducing an intelligent tool inclination optimization algorithm. Furthermore, aspects of micro deep-hole drilling of SMAs are discussed. Tools with diameters as small as 0.5 mm are used. The possible length-to-diameter ratio reaches up to 50. This process offers new possibilities in the manufacturing of microstents. The study concentrates on the influence of the cutting speed, the feed and the tool design on the tool wear and the quality of the drilled holes.

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.

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.

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

Investigation of the shape transferability of nanoscale multi-tip diamond tools in the diamond turning of nanostructures

NASA Astrophysics Data System (ADS)

Luo, Xichun; Tong, Zhen; Liang, Yingchun

2014-12-01

In this article, the shape transferability of using nanoscale multi-tip diamond tools in the diamond turning for scale-up manufacturing of nanostructures has been demonstrated. Atomistic multi-tip diamond tool models were built with different tool geometries in terms of the difference in the tip cross-sectional shape, tip angle, and the feature of tool tip configuration, to determine their effect on the applied forces and the machined nano-groove geometries. The quality of machined nanostructures was characterized by the thickness of the deformed layers and the dimensional accuracy achieved. Simulation results show that diamond turning using nanoscale multi-tip tools offers tremendous shape transferability in machining nanostructures. Both periodic and non-periodic nano-grooves with different cross-sectional shapes can be successfully fabricated using the multi-tip tools. A hypothesis of minimum designed ratio of tool tip distance to tip base width (L/Wf) of the nanoscale multi-tip diamond tool for the high precision machining of nanostructures was proposed based on the analytical study of the quality of the nanostructures fabricated using different types of the multi-tip tools. Nanometric cutting trials using nanoscale multi-tip diamond tools (different in L/Wf) fabricated by focused ion beam (FIB) were then conducted to verify the hypothesis. The investigations done in this work imply the potential of using the nanoscale multi-tip diamond tool for the deterministic fabrication of period and non-periodic nanostructures, which opens up the feasibility of using the process as a versatile manufacturing technique in nanotechnology.

Pre-Finishing of SiC for Optical Applications

NASA Technical Reports Server (NTRS)

Rozzi, Jay; Clavier, Odile; Gagne, John

2011-01-01

13 Manufacturing & Prototyping A method is based on two unique processing steps that are both based on deterministic machining processes using a single-point diamond turning (SPDT) machine. In the first step, a high-MRR (material removal rate) process is used to machine the part within several microns of the final geometry. In the second step, a low-MRR process is used to machine the part to near optical quality using a novel ductile regime machining (DRM) process. DRM is a deterministic machining process associated with conditions under high hydrostatic pressures and very small depths of cut. Under such conditions, using high negative-rake angle cutting tools, the high-pressure region near the tool corresponds to a plastic zone, where even a brittle material will behave in a ductile manner. In the high-MRR processing step, the objective is to remove material with a sufficiently high rate such that the process is economical, without inducing large-scale subsurface damage. A laser-assisted machining approach was evaluated whereby a CO2 laser was focused in advance of the cutting tool. While CVD (chemical vapor deposition) SiC was successfully machined with this approach, the cutting forces were substantially higher than cuts at room temperature under the same machining conditions. During the experiments, the expansion of the part and the tool due to the heating was carefully accounted for. The higher cutting forces are most likely due to a small reduction in the shear strength of the material compared with a larger increase in friction forces due to the thermal softening effect. The key advantage is that the hybrid machine approach has the potential to achieve optical quality without the need for a separate optical finishing step. Also, this method is scalable, so one can easily progress from machining 50-mm-diameter samples to the 250-mm-diameter mirror that NASA desires.

Analytical Model-Based Design Optimization of a Transverse Flux Machine

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

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

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.

Computer-aided design/computer-aided manufacturing skull base drill.

PubMed

Couldwell, William T; MacDonald, Joel D; Thomas, Charles L; Hansen, Bradley C; Lapalikar, Aniruddha; Thakkar, Bharat; Balaji, Alagar K

2017-05-01

The authors have developed a simple device for computer-aided design/computer-aided manufacturing (CAD-CAM) that uses an image-guided system to define a cutting tool path that is shared with a surgical machining system for drilling bone. Information from 2D images (obtained via CT and MRI) is transmitted to a processor that produces a 3D image. The processor generates code defining an optimized cutting tool path, which is sent to a surgical machining system that can drill the desired portion of bone. This tool has applications for bone removal in both cranial and spine neurosurgical approaches. Such applications have the potential to reduce surgical time and associated complications such as infection or blood loss. The device enables rapid removal of bone within 1 mm of vital structures. The validity of such a machining tool is exemplified in the rapid (< 3 minutes machining time) and accurate removal of bone for transtemporal (for example, translabyrinthine) approaches.

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.

Cognitive learning: a machine learning approach for automatic process characterization from design

NASA Astrophysics Data System (ADS)

Foucher, J.; Baderot, J.; Martinez, S.; Dervilllé, A.; Bernard, G.

2018-03-01

Cutting edge innovation requires accurate and fast process-control to obtain fast learning rate and industry adoption. Current tools available for such task are mainly manual and user dependent. We present in this paper cognitive learning, which is a new machine learning based technique to facilitate and to speed up complex characterization by using the design as input, providing fast training and detection time. We will focus on the machine learning framework that allows object detection, defect traceability and automatic measurement tools.

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.

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.

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.

Precision tool holder with flexure-adjustable, three degrees of freedom for a four-axis lathe

DOEpatents

Bono, Matthew J [Pleasanton, CA; Hibbard, Robin L [Livermore, CA

2008-03-04

A precision tool holder for precisely positioning a single point cutting tool on 4-axis lathe, such that the center of the radius of the tool nose is aligned with the B-axis of the machine tool, so as to facilitate the machining of precision meso-scale components with complex three-dimensional shapes with sub-.mu.m accuracy on a four-axis lathe. The device is designed to fit on a commercial diamond turning machine and can adjust the cutting tool position in three orthogonal directions with sub-micrometer resolution. In particular, the tool holder adjusts the tool position using three flexure-based mechanisms, with two flexure mechanisms adjusting the lateral position of the tool to align the tool with the B-axis, and a third flexure mechanism adjusting the height of the tool. Preferably, the flexures are driven by manual micrometer adjusters. In this manner, this tool holder simplifies the process of setting a tool with sub-.mu.m accuracy, to substantially reduce the time required to set the tool.

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.

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.

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 addition to the effect of cutting parameters. Thus, promising results were obtained which showed a very good agreement with the experimental results. Moreover, a more advanced model was constructed, by adding the tool wear as another variable to the previous model. Therefore, a new model was proposed for estimating the remaining life of worn inserts under different cutting conditions, using the current tool wear data as an input. The results of this model were validated with the experimental results. The estimated results were well consistent with the results obtained from the experiments.

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.

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.

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.

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.

Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

PubMed Central

Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

2014-01-01

Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability. PMID:25405514

Force sensor based tool condition monitoring using a heterogeneous ensemble learning model.

PubMed

Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

2014-11-14

Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

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

Bunshah, R.F.; Shabaik, A.H.

The process of Activated Reactive Evaporation is used to synthesize superhard materials like carbides, oxides, nitrides and ultrafine grain cermets. The deposits are characterized by hardness, microstructure, microprobe analysis for chemistry and lattice parameter measurements. The synthesis and characterization of TiC-Ni cermets and Al/sub 2/O/sub 3/ are given. High speed steel tool coated with TiC, TiC-Ni and TaC are tested for machining performance at different speeds and feeds. The machining evaluation and the selection of coatings is based on the rate of deterioration of the coating tool temperature, and cutting forces. Tool life tests show coated high speed steel toolsmore » having 150 to 300% improvement in tool life compared to uncoated tools. Variability in the quality of the ground edge on high speed steel inserts produce a great scatter in the machining evaluation data.« less

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.

Progress in development of coated indexable cemented carbide inserts for machining of iron based work piece materials

NASA Astrophysics Data System (ADS)

Czettl, C.; Pohler, M.

2016-03-01

Increasing demands on material properties of iron based work piece materials, e.g. for the turbine industry, complicate the machining process and reduce the lifetime of the cutting tools. Therefore, improved tool solutions, adapted to the requirements of the desired application have to be developed. Especially, the interplay of macro- and micro geometry, substrate material, coating and post treatment processes is crucial for the durability of modern high performance tool solutions. Improved and novel analytical methods allow a detailed understanding of material properties responsible for the wear behaviour of the tools. Those support the knowledge based development of tailored cutting materials for selected applications. One important factor for such a solution is the proper choice of coating material, which can be synthesized by physical or chemical vapor deposition techniques. Within this work an overview of state-of-the-art coated carbide grades is presented and application examples are shown to demonstrate their high efficiency. Machining processes for a material range from cast iron, low carbon steels to high alloyed steels are covered.

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

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.

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.

[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.

minimega v. 3.0

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

Crussell, Jonathan; Erickson, Jeremy; Fritz, David

minimega is an emulytics platform for creating testbeds of networked devices. The platoform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. minimega allows experiments to be brought up quickly with almost no configuration. minimega also includes tools for simple cluster, management, as well as tools for creating Linux-based virtual machines. This release of minimega includes new emulated sensors for Android devices to improve the fidelity of testbeds that include mobile devices. Emulated sensors include GPS and

Computer Simulation Of An In-Process Surface Finish Sensor.

NASA Astrophysics Data System (ADS)

Rakels, Jan H.

1987-01-01

It is generally accepted, that optical methods are the most promising for the in-process measurement of surface finish. These methods have the advantages of being non-contacting and fast data acquisition. Furthermore, these optical instruments can be easily retrofitted on existing machine-tools. In the Micro-Engineering Centre at the University of Warwick, an optical sensor has been developed which can measure the rms roughness, slope and wavelength of turned and precision ground surfaces during machining. The operation of this device is based upon the Kirchhoff-Fresnel diffraction integral. Application of this theory to ideal turned and ground surfaces is straightforward, and indeed the calculated diffraction patterns are in close agreement with patterns produced by an actual optical instrument. Since it is mathematically difficult to introduce real machine-tool behaviour into the diffraction integral, a computer program has been devised, which simulates the operation of the optical sensor. The program produces a diffraction pattern as a graphical output. Comparison between computer generated and actual diffraction patterns of the same surfaces show a high correlation. The main aim of this program is to construct an atlas, which maps known machine-tool errors versus optical diffraction patterns. This atlas can then be used for machine-tool condition diagnostics. It has been found that optical monitoring is very sensitive to minor defects. Therefore machine-tool detoriation can be detected before it is detrimental.

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

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 and burr formations through intermittent cutting. Combining the AFM probe based machining with vibration-assisted machining enhanced nano mechanical machining processes by improving the accuracy, productivity and surface finishes. In this study, several scratching tests are performed with a single crystal diamond AFM probe to investigate the cutting characteristics and model the ploughing cutting forces. Calibration of the probe for lateral force measurements, which is essential, is also extended through the force balance method. Furthermore, vibration-assisted machining system is developed and applied to fabricate different materials to overcome some of the limitations of the AFM probe based single point nano mechanical machining. The novelty of this study includes the application of vibration-assisted AFM probe based nano scale machining to fabricate micro/nano scale features, calibration of an AFM by considering different factors, and the investigation of the nano scale material removal process from a different perspective.

4. Credit JPL. Original 4" x 5" black and white ...

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

4. Credit JPL. Original 4" x 5" black and white negative housed in the JPL Archives, Pasadena, California. This interior view displays the machine shop in the Administration/Shops Building (the compass angle of the view is undetermined). Looking clockwise from the lower left, the machine tools in view are a power hacksaw, a heat-treatment oven (with white gloves on top), a large hydraulic press with a tool grinder at its immediate right; along the wall in the back of the view are various unidentified machine tool attachments and a vertical milling machine. In the background, a machinist is operating a radial drilling machine, to the right of which is a small drill press. To the lower right, another machinist is operating a Pratt & Whitney engine lathe; behind the operator stand a workbench and vertical bandsaw (JPL negative no. 384-10939, 29 July 1975). - Jet Propulsion Laboratory Edwards Facility, Administration & Shops Building, Edwards Air Force Base, Boron, Kern County, CA

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…

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.

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.

Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data.

PubMed

Piccinini, Filippo; Balassa, Tamas; Szkalisity, Abel; Molnar, Csaba; Paavolainen, Lassi; Kujala, Kaisa; Buzas, Krisztina; Sarazova, Marie; Pietiainen, Vilja; Kutay, Ulrike; Smith, Kevin; Horvath, Peter

2017-06-28

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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

Bunshah, R.F.; Shabaik, A.H.

The process of Activated Reactive Evaporation is used to synthesize superhard materials like carbides, oxides, nitrides, ultrafine grain cermets. The deposits are characterized by hardness, microstructure and lattice parameter measurements. The synthesis and characterization of TiC-Ni cermets, Al/sub 2/O/sub 3/ and VC-TiC alloy carbides is given. Tools of different coating characteristics are tested for machining performance at different speeds and feeds. The machining evaluation and the selection of coatings is based on the rate of deterioration of the costing, tool temperature, and cutting forces. Tool life tests show coated high speed steel tools show a 300% improvement in tool life.more » (Author) (GRA)« less

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

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

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.

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

Micro electrical discharge milling using deionized water as a dielectric fluid

NASA Astrophysics Data System (ADS)

Chung, Do Kwan; Kim, Bo Hyun; Chu, Chong Nam

2007-05-01

In electrical discharge machining, dielectric fluid is an important factor affecting machining characteristics. Generally, kerosene and deionized water have been used as dielectric fluids. In micro electrical discharge milling, which uses a micro electrode as a tool, the wear of the tool electrode decreases the machining accuracy. However, the use of deionized water instead of kerosene can reduce the tool wear and increase the machining speed. This paper investigates micro electrical discharge milling using deionized water. Deionized water with high resistivity was used to minimize the machining gap. Machining characteristics such as the tool wear, machining gap and machining rate were investigated according to resistivity of deionized water. As the resistivity of deionized water decreased, the tool wear was reduced, but the machining gap increased due to electrochemical dissolution. Micro hemispheres were machined for the purpose of investigating machining efficiency between dielectric fluids, kerosene and deionized water.

Estimation of tool wear during CNC milling using neural network-based sensor fusion

NASA Astrophysics Data System (ADS)

Ghosh, N.; Ravi, Y. B.; Patra, A.; Mukhopadhyay, S.; Paul, S.; Mohanty, A. R.; Chattopadhyay, A. B.

2007-01-01

Cutting tool wear degrades the product quality in manufacturing processes. Monitoring tool wear value online is therefore needed to prevent degradation in machining quality. Unfortunately there is no direct way of measuring the tool wear online. Therefore one has to adopt an indirect method wherein the tool wear is estimated from several sensors measuring related process variables. In this work, a neural network-based sensor fusion model has been developed for tool condition monitoring (TCM). Features extracted from a number of machining zone signals, namely cutting forces, spindle vibration, spindle current, and sound pressure level have been fused to estimate the average flank wear of the main cutting edge. Novel strategies such as, signal level segmentation for temporal registration, feature space filtering, outlier removal, and estimation space filtering have been proposed. The proposed approach has been validated by both laboratory and industrial implementations.

Omega-X micromachining system

DOEpatents

Miller, Donald M.

1978-01-01

A micromachining tool system with X- and omega-axes is used to machine spherical, aspherical, and irregular surfaces with a maximum contour error of 100 nonometers (nm) and surface waviness of no more than 0.8 nm RMS. The omega axis, named for the angular measurement of the rotation of an eccentric mechanism supporting one end of a tool bar, enables the pulse increments of the tool toward the workpiece to be as little as 0 to 4.4 nm. A dedicated computer coordinates motion in the two axes to produce the workpiece contour. Inertia is reduced by reducing the mass pulsed toward the workpiece to about one-fifth of its former value. The tool system includes calibration instruments to calibrate the micromachining tool system. Backlash is reduced and flexing decreased by using a rotary table and servomotor to pulse the tool in the omega-axis instead of a ball screw mechanism. A thermally-stabilized spindle rotates the workpiece and is driven by a motor not mounted on the micromachining tool base through a torque-smoothing pulley and vibrationless rotary coupling. Abbe offset errors are almost eliminated by tool setting and calibration at spindle center height. Tool contour and workpiece contour are gaged on the machine; this enables the source of machining errors to be determined more readily, because the workpiece is gaged before its shape can be changed by removal from the machine.

Cardiac imaging: working towards fully-automated machine analysis & interpretation.

PubMed

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-03-01

Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

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.

Virtual Manufacturing Techniques Designed and Applied to Manufacturing Activities in the Manufacturing Integration and Technology Branch

NASA Technical Reports Server (NTRS)

Shearrow, Charles A.

1999-01-01

One of the identified goals of EM3 is to implement virtual manufacturing by the time the year 2000 has ended. To realize this goal of a true virtual manufacturing enterprise the initial development of a machinability database and the infrastructure must be completed. This will consist of the containment of the existing EM-NET problems and developing machine, tooling, and common materials databases. To integrate the virtual manufacturing enterprise with normal day to day operations the development of a parallel virtual manufacturing machinability database, virtual manufacturing database, virtual manufacturing paradigm, implementation/integration procedure, and testable verification models must be constructed. Common and virtual machinability databases will include the four distinct areas of machine tools, available tooling, common machine tool loads, and a materials database. The machine tools database will include the machine envelope, special machine attachments, tooling capacity, location within NASA-JSC or with a contractor, and availability/scheduling. The tooling database will include available standard tooling, custom in-house tooling, tool properties, and availability. The common materials database will include materials thickness ranges, strengths, types, and their availability. The virtual manufacturing databases will consist of virtual machines and virtual tooling directly related to the common and machinability databases. The items to be completed are the design and construction of the machinability databases, virtual manufacturing paradigm for NASA-JSC, implementation timeline, VNC model of one bridge mill and troubleshoot existing software and hardware problems with EN4NET. The final step of this virtual manufacturing project will be to integrate other production sites into the databases bringing JSC's EM3 into a position of becoming a clearing house for NASA's digital manufacturing needs creating a true virtual manufacturing enterprise.

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.

Software Tools for Emittance Measurement and Matching for 12 GeV CEBAF

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

Turner, Dennis L.

2016-05-01

This paper discusses model-driven setup of the Continuous Electron Beam Accelerator Facility (CEBAF) for the 12GeV era, focusing on qsUtility. qsUtility is a set of software tools created to perform emittance measurements, analyze those measurements, and compute optics corrections based upon the measurements.qsUtility was developed as a toolset to facilitate reducing machine configuration time and reproducibility by way of an accurate accelerator model, and to provide Operations staff with tools to measure and correct machine optics with little or no assistance from optics experts.

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.

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.

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 of wet abrasive jet machining.

Machine learning for the meta-analyses of microbial pathogens' volatile signatures.

PubMed

Palma, Susana I C J; Traguedo, Ana P; Porteira, Ana R; Frias, Maria J; Gamboa, Hugo; Roque, Ana C A

2018-02-20

Non-invasive and fast diagnostic tools based on volatolomics hold great promise in the control of infectious diseases. However, the tools to identify microbial volatile organic compounds (VOCs) discriminating between human pathogens are still missing. Artificial intelligence is increasingly recognised as an essential tool in health sciences. Machine learning algorithms based in support vector machines and features selection tools were here applied to find sets of microbial VOCs with pathogen-discrimination power. Studies reporting VOCs emitted by human microbial pathogens published between 1977 and 2016 were used as source data. A set of 18 VOCs is sufficient to predict the identity of 11 microbial pathogens with high accuracy (77%), and precision (62-100%). There is one set of VOCs associated with each of the 11 pathogens which can predict the presence of that pathogen in a sample with high accuracy and precision (86-90%). The implemented pathogen classification methodology supports future database updates to include new pathogen-VOC data, which will enrich the classifiers. The sets of VOCs identified potentiate the improvement of the selectivity of non-invasive infection diagnostics using artificial olfaction devices.

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.

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.

Modeling of Principal Flank Wear: An Empirical Approach Combining the Effect of Tool, Environment and Workpiece Hardness

NASA Astrophysics Data System (ADS)

Mia, Mozammel; Al Bashir, Mahmood; Dhar, Nikhil Ranjan

2016-10-01

Hard turning is increasingly employed in machining, lately, to replace time-consuming conventional turning followed by grinding process. An excessive amount of tool wear in hard turning is one of the main hurdles to be overcome. Many researchers have developed tool wear model, but most of them developed it for a particular work-tool-environment combination. No aggregate model is developed that can be used to predict the amount of principal flank wear for specific machining time. An empirical model of principal flank wear (VB) has been developed for the different hardness of workpiece (HRC40, HRC48 and HRC56) while turning by coated carbide insert with different configurations (SNMM and SNMG) under both dry and high pressure coolant conditions. Unlike other developed model, this model includes the use of dummy variables along with the base empirical equation to entail the effect of any changes in the input conditions on the response. The base empirical equation for principal flank wear is formulated adopting the Exponential Associate Function using the experimental results. The coefficient of dummy variable reflects the shifting of the response from one set of machining condition to another set of machining condition which is determined by simple linear regression. The independent cutting parameters (speed, rate, depth of cut) are kept constant while formulating and analyzing this model. The developed model is validated with different sets of machining responses in turning hardened medium carbon steel by coated carbide inserts. For any particular set, the model can be used to predict the amount of principal flank wear for specific machining time. Since the predicted results exhibit good resemblance with experimental data and the average percentage error is <10 %, this model can be used to predict the principal flank wear for stated conditions.

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)…

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.

Solution of task related to control of swiss-type automatic lathe to get planes parallel to part axis

NASA Astrophysics Data System (ADS)

Tabekina, N. A.; Chepchurov, M. S.; Evtushenko, E. I.; Dmitrievsky, B. S.

2018-05-01

The work solves the problem of automation of machining process namely turning to produce parts having the planes parallel to an axis of rotation of part without using special tools. According to the results, the availability of the equipment of a high speed electromechanical drive to control the operative movements of lathe machine will enable one to get the planes parallel to the part axis. The method of getting planes parallel to the part axis is based on the mathematical model, which is presented as functional dependency between the conveying velocity of the driven element and the time. It describes the operative movements of lathe machine all over the tool path. Using the model of movement of the tool, it has been found that the conveying velocity varies from the maximum to zero value. It will allow one to carry out the reverse of the drive. The scheme of tool placement regarding the workpiece has been proposed for unidirectional movement of the driven element at high conveying velocity. The control method of CNC machines can be used for getting geometrically complex parts on the lathe without using special milling tools.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

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.

On-machine precision preparation and dressing of ball-headed diamond wheel for the grinding of fused silica

NASA Astrophysics Data System (ADS)

Chen, Mingjun; Li, Ziang; Yu, Bo; Peng, Hui; Fang, Zhen

2013-09-01

In the grinding of high quality fused silica parts with complex surface or structure using ball-headed metal bonded diamond wheel with small diameter, the existing dressing methods are not suitable to dress the ball-headed diamond wheel precisely due to that they are either on-line in process dressing which may causes collision problem or without consideration for the effects of the tool setting error and electrode wear. An on-machine precision preparation and dressing method is proposed for ball-headed diamond wheel based on electrical discharge machining. By using this method the cylindrical diamond wheel with small diameter is manufactured to hemispherical-headed form. The obtained ball-headed diamond wheel is dressed after several grinding passes to recover geometrical accuracy and sharpness which is lost due to the wheel wear. A tool setting method based on high precision optical system is presented to reduce the wheel center setting error and dimension error. The effect of electrode tool wear is investigated by electrical dressing experiments, and the electrode tool wear compensation model is established based on the experimental results which show that the value of wear ratio coefficient K' tends to be constant with the increasing of the feed length of electrode and the mean value of K' is 0.156. Grinding experiments of fused silica are carried out on a test bench to evaluate the performance of the preparation and dressing method. The experimental results show that the surface roughness of the finished workpiece is 0.03 μm. The effect of the grinding parameter and dressing frequency on the surface roughness is investigated based on the measurement results of the surface roughness. This research provides an on-machine preparation and dressing method for ball-headed metal bonded diamond wheel used in the grinding of fused silica, which provides a solution to the tool setting method and the effect of electrode tool wear.

Thermocouple and infrared sensor-based measurement of temperature distribution in metal cutting.

PubMed

Kus, Abdil; Isik, Yahya; Cakir, M Cemal; Coşkun, Salih; Özdemir, Kadir

2015-01-12

In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining.

Thermocouple and Infrared Sensor-Based Measurement of Temperature Distribution in Metal Cutting

PubMed Central

Kus, Abdil; Isik, Yahya; Cakir, M. Cemal; Coşkun, Salih; Özdemir, Kadir

2015-01-01

In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining. PMID:25587976

The Rack-Gear Tool Generation Modelling. Non-Analytical Method Developed in CATIA, Using the Relative Generating Trajectories Method

NASA Astrophysics Data System (ADS)

Teodor, V. G.; Baroiu, N.; Susac, F.; Oancea, N.

2016-11-01

The modelling of a curl of surfaces associated with a pair of rolling centrodes, when it is known the profile of the rack-gear's teeth profile, by direct measuring, as a coordinate matrix, has as goal the determining of the generating quality for an imposed kinematics of the relative motion of tool regarding the blank. In this way, it is possible to determine the generating geometrical error, as a base of the total error. The generation modelling allows highlighting the potential errors of the generating tool, in order to correct its profile, previously to use the tool in machining process. A method developed in CATIA is proposed, based on a new method, namely the method of “relative generating trajectories”. They are presented the analytical foundation, as so as some application for knows models of rack-gear type tools used on Maag teething machines.

Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations.

PubMed

Zhang, Cunji; Yao, Xifan; Zhang, Jianming; Jin, Hong

2016-05-31

Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM) is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z) are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time-frequency domains. The key features are selected based on Pearson's Correlation Coefficient (PCC). The Neuro-Fuzzy Network (NFN) is adopted to predict the tool wear and Remaining Useful Life (RUL). In comparison with Back Propagation Neural Network (BPNN) and Radial Basis Function Network (RBFN), the results show that the NFN has the best performance in the prediction of tool wear and RUL.

Effect of Cutting Parameters on Thrust Force and Surface Roughness in Drilling of Al-2219/B4C/Gr Metal Matrix Composites

NASA Astrophysics Data System (ADS)

Ravindranath, V. M.; Basavarajappa, G. S. Shiva Shankar S.; Suresh, R.

2016-09-01

In aluminium matrix composites, reinforcement of hard ceramic particle present inside the matrix which causes tool wear, high cutting forces and poor surface finish during machining. This paper focuses on effect of cutting parameters on thrust force, surface roughness and burr height during drilling of MMCs. In the present work, discuss the influence of spindle speed and feed rate on drilling the pure base alloy (Al-2219), mono composite (Al- 2219+8% B4C) and hybrid composite (Al-2219+8%B4C+3%Gr). The composites were fabricated using liquid metallurgy route. The drilling experiments were conducted by CNC machine with TiN coated HSS tool, M42 (Cobalt grade) and carbide tools at various spindle speeds and feed rates. The thrust force, surface roughness and burr height of the drilled hole were investigated in mono composite and hybrid composite containing graphite particles, the experimental results show that the feed rate has more influence on thrust force and surface roughness. Lesser thrust force and discontinuous chips were produced during machining of hybrid composites when compared with mono and base alloy during drilling process. It is due to solid lubricant property of graphite which reduces the lesser thrust force, burr height and lower surface roughness. When machining with Carbide tool at low feed and high speeds good surface finish was obtained compared to other two types of cutting tool materials.

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.

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.

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.

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...

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

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.

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.

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.

Volumetric error modeling, identification and compensation based on screw theory for a large multi-axis propeller-measuring machine

NASA Astrophysics Data System (ADS)

Zhong, Xuemin; Liu, Hongqi; Mao, Xinyong; Li, Bin; He, Songping; Peng, Fangyu

2018-05-01

Large multi-axis propeller-measuring machines have two types of geometric error, position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs), which both have significant effects on the volumetric error of the measuring tool relative to the worktable. This paper focuses on modeling, identifying and compensating for the volumetric error of the measuring machine. A volumetric error model in the base coordinate system is established based on screw theory considering all the geometric errors. In order to fully identify all the geometric error parameters, a new method for systematic measurement and identification is proposed. All the PIGEs of adjacent axes and the six PDGEs of the linear axes are identified with a laser tracker using the proposed model. Finally, a volumetric error compensation strategy is presented and an inverse kinematic solution for compensation is proposed. The final measuring and compensation experiments have further verified the efficiency and effectiveness of the measuring and identification method, indicating that the method can be used in volumetric error compensation for large machine tools.

Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

NASA Technical Reports Server (NTRS)

Genuardi, Michael T.

1993-01-01

One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

Reducing tool wear by partial cladding of critical zones in hot form tool by laser metal deposition

NASA Astrophysics Data System (ADS)

Vollmer, Robert; Sommitsch, Christof

2017-10-01

This paper points out a production method to reduce tool wear in hot stamping applications. Usually tool wear can be observed at locally strongly stressed areas superimposed with gliding movement between blank and tool surface. The shown solution is based on a partial laser cladding of the tool surface with a wear resistant coating to increase the lifespan of tool inserts. Preliminary studies showed good results applying a material combination of tungsten carbide particles embedded in a metallic matrix. Different Nickel based alloys welded on hot work tool steel (1.2343) were tested mechanically in the interface zone. The material with the best bonding characteristic is chosen and reinforced with spherical tungsten carbide particles in a second laser welding step. Since the machining of tungsten carbides is very elaborate a special manufacturing strategy is developed to reduce the milling effort as much as possible. On special test specimens milling tests are carried out to proof the machinability. As outlook a tool insert of a b-pillar is coated to perform real hot forming tests.

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

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.

Cardiac imaging: working towards fully-automated machine analysis & interpretation

PubMed Central

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-01-01

Introduction Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation. PMID:28277804

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.

Energetic particle instabilities in fusion plasmas

NASA Astrophysics Data System (ADS)

Sharapov, S. E.; Alper, B.; Berk, H. L.; Borba, D. N.; Breizman, B. N.; Challis, C. D.; Classen, I. G. J.; Edlund, E. M.; Eriksson, J.; Fasoli, A.; Fredrickson, E. D.; Fu, G. Y.; Garcia-Munoz, M.; Gassner, T.; Ghantous, K.; Goloborodko, V.; Gorelenkov, N. N.; Gryaznevich, M. P.; Hacquin, S.; Heidbrink, W. W.; Hellesen, C.; Kiptily, V. G.; Kramer, G. J.; Lauber, P.; Lilley, M. K.; Lisak, M.; Nabais, F.; Nazikian, R.; Nyqvist, R.; Osakabe, M.; Perez von Thun, C.; Pinches, S. D.; Podesta, M.; Porkolab, M.; Shinohara, K.; Schoepf, K.; Todo, Y.; Toi, K.; Van Zeeland, M. A.; Voitsekhovich, I.; White, R. B.; Yavorskij, V.; TG, ITPA EP; Contributors, JET-EFDA

2013-10-01

Remarkable progress has been made in diagnosing energetic particle instabilities on present-day machines and in establishing a theoretical framework for describing them. This overview describes the much improved diagnostics of Alfvén instabilities and modelling tools developed world-wide, and discusses progress in interpreting the observed phenomena. A multi-machine comparison is presented giving information on the performance of both diagnostics and modelling tools for different plasma conditions outlining expectations for ITER based on our present knowledge.

Accurate Micro-Tool Manufacturing by Iterative Pulsed-Laser Ablation

NASA Astrophysics Data System (ADS)

Warhanek, Maximilian; Mayr, Josef; Dörig, Christian; Wegener, Konrad

2017-12-01

Iterative processing solutions, including multiple cycles of material removal and measurement, are capable of achieving higher geometric accuracy by compensating for most deviations manifesting directly on the workpiece. Remaining error sources are the measurement uncertainty and the repeatability of the material-removal process including clamping errors. Due to the lack of processing forces, process fluids and wear, pulsed-laser ablation has proven high repeatability and can be realized directly on a measuring machine. This work takes advantage of this possibility by implementing an iterative, laser-based correction process for profile deviations registered directly on an optical measurement machine. This way efficient iterative processing is enabled, which is precise, applicable for all tool materials including diamond and eliminates clamping errors. The concept is proven by a prototypical implementation on an industrial tool measurement machine and a nanosecond fibre laser. A number of measurements are performed on both the machine and the processed workpieces. Results show production deviations within 2 μm diameter tolerance.

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.

Investigating the Effect of Approach Angle and Nose Radius on Surface Quality of Inconel 718

NASA Astrophysics Data System (ADS)

Kumar, Sunil; Singh, Dilbag; Kalsi, Nirmal S.

2017-11-01

This experimental work presents a surface quality evaluation of a Nickel-Cr-Fe based Inconel 718 superalloy, which has many applications in the aero engine and turbine components. However, during machining, the early wear of tool leads to decrease in surface quality. The coating on cutting tool plays a significant role in increasing the wear resistance and life of the tool. In this work, the aim is to study the surface quality of Inconel 718 with TiAlN-coated carbide tools. Influence of various geometrical parameters (tool nose radius, approach angle) and machining variables (cutting velocity, feed rate) on the quality of machined surface (surface roughness) was determined by using central composite design (CCD) matrix. The mathematical model of the same was developed. Analysis of variance was used to find the significance of the parameters. Results showed that the tool nose radius and feed were the main active factors. The present experiment accomplished that TiAlN-coated carbide inserts result in better surface quality as compared with uncoated carbide inserts.

Machine learning models for lipophilicity and their domain of applicability.

PubMed

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Laak, Antonius Ter; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-01-01

Unfavorable lipophilicity and water solubility cause many drug failures; therefore these properties have to be taken into account early on in lead discovery. Commercial tools for predicting lipophilicity usually have been trained on small and neutral molecules, and are thus often unable to accurately predict in-house data. Using a modern Bayesian machine learning algorithm--a Gaussian process model--this study constructs a log D7 model based on 14,556 drug discovery compounds of Bayer Schering Pharma. Performance is compared with support vector machines, decision trees, ridge regression, and four commercial tools. In a blind test on 7013 new measurements from the last months (including compounds from new projects) 81% were predicted correctly within 1 log unit, compared to only 44% achieved by commercial software. Additional evaluations using public data are presented. We consider error bars for each method (model based error bars, ensemble based, and distance based approaches), and investigate how well they quantify the domain of applicability of each model.

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.

A Flexure-Based Tool Holder for Sub-(micro)m Positioning of a Single Point Cutting Tool on a Four-axis Lathe

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

Bono, M J; Hibbard, R L

2005-12-05

A tool holder was designed to facilitate the machining of precision meso-scale components with complex three-dimensional shapes with sub-{micro}m accuracy on a four-axis lathe. A four-axis lathe incorporates a rotary table that allows the cutting tool to swivel with respect to the workpiece to enable the machining of complex workpiece forms, and accurately machining complex meso-scale parts often requires that the cutting tool be aligned precisely along the axis of rotation of the rotary table. The tool holder designed in this study has greatly simplified the process of setting the tool in the correct location with sub-{micro}m precision. The toolmore » holder adjusts the tool position using flexures that were designed using finite element analyses. Two flexures adjust the lateral position of the tool to align the center of the nose of the tool with the axis of rotation of the B-axis, and another flexure adjusts the height of the tool. The flexures are driven by manual micrometer adjusters, each of which provides a minimum increment of motion of 20 nm. This tool holder has simplified the process of setting a tool with sub-{micro}m accuracy, and it has significantly reduced the time required to set a tool.« less

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

Phenomenology tools on cloud infrastructures using OpenStack

NASA Astrophysics Data System (ADS)

Campos, I.; Fernández-del-Castillo, E.; Heinemeyer, S.; Lopez-Garcia, A.; Pahlen, F.; Borges, G.

2013-04-01

We present a new environment for computations in particle physics phenomenology employing recent developments in cloud computing. On this environment users can create and manage "virtual" machines on which the phenomenology codes/tools can be deployed easily in an automated way. We analyze the performance of this environment based on "virtual" machines versus the utilization of physical hardware. In this way we provide a qualitative result for the influence of the host operating system on the performance of a representative set of applications for phenomenology calculations.

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.

Computer Aided Simulation Machining Programming In 5-Axis Nc Milling Of Impeller Leaf

NASA Astrophysics Data System (ADS)

Huran, Liu

At present, cad/cam (computer-aided design and manufacture) have fine wider and wider application in mechanical industry. For the complex surfaces, the traditional machine tool can no longer satisfy the requirement of such complex task. Only by the help of cad/cam can fulfill the requirement. The machining of the vane surface of the impeller leaf has been considered as the hardest challenge. Because of their complex shape, the 5-axis cnc machine tool is needed for the machining of such parts. The material is hard to cut, the requirement for the surface finish and clearance is very high, so that the manufacture quality of impeller leaf represent the level of 5-axis machining. This paper opened a new field in machining the complicated surface, based on a relatively more rigid mathematical basis. The theory presented here is relatively more systematical. Since the lack of theoretical guidance, in the former research, people have to try in machining many times. Such case will be changed. The movement of the cutter determined by this method is definite, and the residual is the smallest while the times of travel is the fewest. The criterion is simple and the calculation is easy.

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.

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.

Hybrid ABC Optimized MARS-Based Modeling of the Milling Tool Wear from Milling Run Experimental Data

PubMed Central

García Nieto, Paulino José; García-Gonzalo, Esperanza; Ordóñez Galán, Celestino; Bernardo Sánchez, Antonio

2016-01-01

Milling cutters are important cutting tools used in milling machines to perform milling operations, which are prone to wear and subsequent failure. In this paper, a practical new hybrid model to predict the milling tool wear in a regular cut, as well as entry cut and exit cut, of a milling tool is proposed. The model was based on the optimization tool termed artificial bee colony (ABC) in combination with multivariate adaptive regression splines (MARS) technique. This optimization mechanism involved the parameter setting in the MARS training procedure, which significantly influences the regression accuracy. Therefore, an ABC–MARS-based model was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. Regression with optimal hyperparameters was performed and a determination coefficient of 0.94 was obtained. The ABC–MARS-based model's goodness of fit to experimental data confirmed the good performance of this model. This new model also allowed us to ascertain the most influential parameters on the milling tool flank wear with a view to proposing milling machine's improvements. Finally, conclusions of this study are exposed. PMID:28787882

Hybrid ABC Optimized MARS-Based Modeling of the Milling Tool Wear from Milling Run Experimental Data.

PubMed

García Nieto, Paulino José; García-Gonzalo, Esperanza; Ordóñez Galán, Celestino; Bernardo Sánchez, Antonio

2016-01-28

Milling cutters are important cutting tools used in milling machines to perform milling operations, which are prone to wear and subsequent failure. In this paper, a practical new hybrid model to predict the milling tool wear in a regular cut, as well as entry cut and exit cut, of a milling tool is proposed. The model was based on the optimization tool termed artificial bee colony (ABC) in combination with multivariate adaptive regression splines (MARS) technique. This optimization mechanism involved the parameter setting in the MARS training procedure, which significantly influences the regression accuracy. Therefore, an ABC-MARS-based model was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc . Regression with optimal hyperparameters was performed and a determination coefficient of 0.94 was obtained. The ABC-MARS-based model's goodness of fit to experimental data confirmed the good performance of this model. This new model also allowed us to ascertain the most influential parameters on the milling tool flank wear with a view to proposing milling machine's improvements. Finally, conclusions of this study are exposed.

Multiple performance characteristics optimization for Al 7075 on electric discharge drilling by Taguchi grey relational theory

NASA Astrophysics Data System (ADS)

Khanna, Rajesh; Kumar, Anish; Garg, Mohinder Pal; Singh, Ajit; Sharma, Neeraj

2015-12-01

Electric discharge drill machine (EDDM) is a spark erosion process to produce micro-holes in conductive materials. This process is widely used in aerospace, medical, dental and automobile industries. As for the performance evaluation of the electric discharge drilling machine, it is very necessary to study the process parameters of machine tool. In this research paper, a brass rod 2 mm diameter was selected as a tool electrode. The experiments generate output responses such as tool wear rate (TWR). The best parameters such as pulse on-time, pulse off-time and water pressure were studied for best machining characteristics. This investigation presents the use of Taguchi approach for better TWR in drilling of Al-7075. A plan of experiments, based on L27 Taguchi design method, was selected for drilling of material. Analysis of variance (ANOVA) shows the percentage contribution of the control factor in the machining of Al-7075 in EDDM. The optimal combination levels and the significant drilling parameters on TWR were obtained. The optimization results showed that the combination of maximum pulse on-time and minimum pulse off-time gives maximum MRR.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

NASA Astrophysics Data System (ADS)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

A Cooperative Approach to Virtual Machine Based Fault Injection

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

Naughton III, Thomas J; Engelmann, Christian; Vallee, Geoffroy R

Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target con- text is increased due to the separation between host and guest (VM).more » We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof- of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.« less

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.

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.

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

Toward an Improvement of the Analysis of Neural Coding.

PubMed

Alegre-Cortés, Javier; Soto-Sánchez, Cristina; Albarracín, Ana L; Farfán, Fernando D; Val-Calvo, Mikel; Ferrandez, José M; Fernandez, Eduardo

2017-01-01

Machine learning and artificial intelligence have strong roots on principles of neural computation. Some examples are the structure of the first perceptron, inspired in the retina, neuroprosthetics based on ganglion cell recordings or Hopfield networks. In addition, machine learning provides a powerful set of tools to analyze neural data, which has already proved its efficacy in so distant fields of research as speech recognition, behavioral states classification, or LFP recordings. However, despite the huge technological advances in neural data reduction of dimensionality, pattern selection, and clustering during the last years, there has not been a proportional development of the analytical tools used for Time-Frequency (T-F) analysis in neuroscience. Bearing this in mind, we introduce the convenience of using non-linear, non-stationary tools, EMD algorithms in particular, for the transformation of the oscillatory neural data (EEG, EMG, spike oscillations…) into the T-F domain prior to its analysis with machine learning tools. We support that to achieve meaningful conclusions, the transformed data we analyze has to be as faithful as possible to the original recording, so that the transformations forced into the data due to restrictions in the T-F computation are not extended to the results of the machine learning analysis. Moreover, bioinspired computation such as brain-machine interface may be enriched from a more precise definition of neuronal coding where non-linearities of the neuronal dynamics are considered.

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.

Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations

PubMed Central

Zhang, Cunji; Yao, Xifan; Zhang, Jianming; Jin, Hong

2016-01-01

Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM) is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z) are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time–frequency domains. The key features are selected based on Pearson’s Correlation Coefficient (PCC). The Neuro-Fuzzy Network (NFN) is adopted to predict the tool wear and Remaining Useful Life (RUL). In comparison with Back Propagation Neural Network (BPNN) and Radial Basis Function Network (RBFN), the results show that the NFN has the best performance in the prediction of tool wear and RUL. PMID:27258277

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.

High performance cutting of aircraft and turbine components

NASA Astrophysics Data System (ADS)

Krämer, A.; Lung, D.; Klocke, F.

2012-04-01

Titanium and nickel-based alloys belong to the group of difficult-to-cut materials. The machining of these high-temperature alloys is characterized by low productivity and low process stability as a result of their physical and mechanical properties. Major problems during the machining of these materials are low applicable cutting speeds due to excessive tool wear, long machining times, and thus high manufacturing costs, as well as the formation of ribbon and snarled chips. Under these conditions automation of the production process is limited. This paper deals with strategies to improve machinability of titanium and nickel-based alloys. Using the example of the nickel-based alloy Inconel 718 high performance cutting with advanced cutting materials, such as PCBN and cutting ceramics, is presented. Afterwards the influence of different cooling strategies, like high-pressure lubricoolant supply and cryogenic cooling, during machining of TiAl6V4 is shown.

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.

Development and validation of methods for man-made machine interface evaluation. [for shuttles and shuttle payloads

NASA Technical Reports Server (NTRS)

Malone, T. B.; Micocci, A.

1975-01-01

The alternate methods of conducting a man-machine interface evaluation are classified as static and dynamic, and are evaluated. A dynamic evaluation tool is presented to provide for a determination of the effectiveness of the man-machine interface in terms of the sequence of operations (task and task sequences) and in terms of the physical characteristics of the interface. This dynamic checklist approach is recommended for shuttle and shuttle payload man-machine interface evaluations based on reduced preparation time, reduced data, and increased sensitivity of critical problems.

Machine learning research 1989-90

NASA Technical Reports Server (NTRS)

Porter, Bruce W.; Souther, Arthur

1990-01-01

Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base.

Development of TIF based figuring algorithm for deterministic pitch tool polishing

NASA Astrophysics Data System (ADS)

Yi, Hyun-Su; Kim, Sug-Whan; Yang, Ho-Soon; Lee, Yun-Woo

2007-12-01

Pitch is perhaps the oldest material used for optical polishing, leaving superior surface texture, and has been used widely in the optics shop floor. However, for its unpredictable controllability of removal characteristics, the pitch tool polishing has been rarely analysed quantitatively and many optics shops rely heavily on optician's "feel" even today. In order to bring a degree of process controllability to the pitch tool polishing, we added motorized tool motions to the conventional Draper type polishing machine and modelled the tool path in the absolute machine coordinate. We then produced a number of Tool Influence Function (TIF) both from an analytical model and a series of experimental polishing runs using the pitch tool. The theoretical TIFs agreed well with the experimental TIFs to the profile accuracy of 79 % in terms of its shape. The surface figuring algorithm was then developed in-house utilizing both theoretical and experimental TIFs. We are currently undertaking a series of trial figuring experiments to prove the performance of the polishing algorithm, and the early results indicate that the highly deterministic material removal control with the pitch tool can be achieved to a certain level of form error. The machine renovation, TIF theory and experimental confirmation, figuring simulation results are reported together with implications to deterministic polishing.

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2015-12-01

Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

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.

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 properties of the modes are also investigated by considering the probability density of the retained modes. Results show a good correlation between numerical and experiment-based identified frequencies. The identified spindle-tool modal properties during machining allow the numerical model to be considered as representative of the real dynamic properties of the system.

Mechanism-Based FE Simulation of Tool Wear in Diamond Drilling of SiCp/Al Composites.

PubMed

Xiang, Junfeng; Pang, Siqin; Xie, Lijing; Gao, Feinong; Hu, Xin; Yi, Jie; Hu, Fang

2018-02-07

The aim of this work is to analyze the micro mechanisms underlying the wear of macroscale tools during diamond machining of SiC p /Al6063 composites and to develop the mechanism-based diamond wear model in relation to the dominant wear behaviors. During drilling, high volume fraction SiC p /Al6063 composites containing Cu, the dominant wear mechanisms of diamond tool involve thermodynamically activated physicochemical wear due to diamond-graphite transformation catalyzed by Cu in air atmosphere and mechanically driven abrasive wear due to high-frequency scrape of hard SiC reinforcement on tool surface. An analytical diamond wear model, coupling Usui abrasive wear model and Arrhenius extended graphitization wear model was proposed and implemented through a user-defined subroutine for tool wear estimates. Tool wear estimate in diamond drilling of SiC p /Al6063 composites was achieved by incorporating the combined abrasive-chemical tool wear subroutine into the coupled thermomechanical FE model of 3D drilling. The developed drilling FE model for reproducing diamond tool wear was validated for feasibility and reliability by comparing numerically simulated tool wear morphology and experimentally observed results after drilling a hole using brazed polycrystalline diamond (PCD) and chemical vapor deposition (CVD) diamond coated tools. A fairly good agreement of experimental and simulated results in cutting forces, chip and tool wear morphologies demonstrates that the developed 3D drilling FE model, combined with a subroutine for diamond tool wear estimate can provide a more accurate analysis not only in cutting forces and chip shape but also in tool wear behavior during drilling SiC p /Al6063 composites. Once validated and calibrated, the developed diamond tool wear model in conjunction with other machining FE models can be easily extended to the investigation of tool wear evolution with various diamond tool geometries and other machining processes in cutting different workpiece materials.

Mechanism-Based FE Simulation of Tool Wear in Diamond Drilling of SiCp/Al Composites

PubMed Central

Xiang, Junfeng; Pang, Siqin; Xie, Lijing; Gao, Feinong; Hu, Xin; Yi, Jie; Hu, Fang

2018-01-01

The aim of this work is to analyze the micro mechanisms underlying the wear of macroscale tools during diamond machining of SiCp/Al6063 composites and to develop the mechanism-based diamond wear model in relation to the dominant wear behaviors. During drilling, high volume fraction SiCp/Al6063 composites containing Cu, the dominant wear mechanisms of diamond tool involve thermodynamically activated physicochemical wear due to diamond-graphite transformation catalyzed by Cu in air atmosphere and mechanically driven abrasive wear due to high-frequency scrape of hard SiC reinforcement on tool surface. An analytical diamond wear model, coupling Usui abrasive wear model and Arrhenius extended graphitization wear model was proposed and implemented through a user-defined subroutine for tool wear estimates. Tool wear estimate in diamond drilling of SiCp/Al6063 composites was achieved by incorporating the combined abrasive-chemical tool wear subroutine into the coupled thermomechanical FE model of 3D drilling. The developed drilling FE model for reproducing diamond tool wear was validated for feasibility and reliability by comparing numerically simulated tool wear morphology and experimentally observed results after drilling a hole using brazed polycrystalline diamond (PCD) and chemical vapor deposition (CVD) diamond coated tools. A fairly good agreement of experimental and simulated results in cutting forces, chip and tool wear morphologies demonstrates that the developed 3D drilling FE model, combined with a subroutine for diamond tool wear estimate can provide a more accurate analysis not only in cutting forces and chip shape but also in tool wear behavior during drilling SiCp/Al6063 composites. Once validated and calibrated, the developed diamond tool wear model in conjunction with other machining FE models can be easily extended to the investigation of tool wear evolution with various diamond tool geometries and other machining processes in cutting different workpiece materials. PMID:29414839

Accuracy Improvement of Multi-Axis Systems Based on Laser Correction of Volumetric Geometric Errors

NASA Astrophysics Data System (ADS)

Teleshevsky, V. I.; Sokolov, V. A.; Pimushkin, Ya I.

2018-04-01

The article describes a volumetric geometric errors correction method for CNC- controlled multi-axis systems (machine-tools, CMMs etc.). The Kalman’s concept of “Control and Observation” is used. A versatile multi-function laser interferometer is used as Observer in order to measure machine’s error functions. A systematic error map of machine’s workspace is produced based on error functions measurements. The error map results into error correction strategy. The article proposes a new method of error correction strategy forming. The method is based on error distribution within machine’s workspace and a CNC-program postprocessor. The postprocessor provides minimal error values within maximal workspace zone. The results are confirmed by error correction of precision CNC machine-tools.

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.

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.

Experimental Investigation of Minimum Quantity Lubrication in Meso-scale Milling with Varying Tool Diameter

NASA Astrophysics Data System (ADS)

Yusof, M. Q. M.; Harun, H. N. S. B.; Bahar, R.

2018-01-01

Minimum quantity lubrication (MQL) is a method that uses a very small amount of liquid to reduce friction between cutting tool and work piece during machining. The implementation of MQL machining has become a viable alternative to flood cooling machining and dry machining. The overall performance has been evaluated during meso-scale milling of mild steel using different diameter milling cutters. Experiments have been conducted under two different lubrication condition: dry and MQL with variable cutting parameters. The tool wear and its surface roughness, machined surfaces microstructure and surface roughness were observed for both conditions. It was found from the results that MQL produced better results compared to dry machining. The 0.5 mm tool has been selected as the most optimum tool diameter to be used with the lowest surface roughness as well as the least flank wear generation. For the workpiece, it was observed that the cutting temperature possesses crucial effect on the microstructure and the surface roughness of the machined surface and bigger diameter tool actually resulted in higher surface roughness. The poor conductivity of the cutting tool may be one of reasons behind.

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.

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.

Real-Time Performance of Mechatronic PZT Module Using Active Vibration Feedback Control.

PubMed

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

2016-09-25

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that seriously compromise the quality of the workpiece. The active vibration control (AVC) device is composed of a host part integrated with sensors and actuators synchronized by a regulator; it is able to make a self-assessment and adjust to alterations in the environment. In particular, an innovative smart actuator has been designed and developed to satisfy machining requirements during active vibration control. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving a machine tool, PZT actuator and controller models. The Hardware in the Loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluated.

Real-Time Performance of Mechatronic PZT Module Using Active Vibration Feedback Control

PubMed Central

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

2016-01-01

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that seriously compromise the quality of the workpiece. The active vibration control (AVC) device is composed of a host part integrated with sensors and actuators synchronized by a regulator; it is able to make a self-assessment and adjust to alterations in the environment. In particular, an innovative smart actuator has been designed and developed to satisfy machining requirements during active vibration control. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving a machine tool, PZT actuator and controller models. The Hardware in the Loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluated. PMID:27681732

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.

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.

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.

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.

Optimization of Coolant Technique Conditions for Machining A319 Aluminium Alloy Using Response Surface Method (RSM)

NASA Astrophysics Data System (ADS)

Zainal Ariffin, S.; Razlan, A.; Ali, M. Mohd; Efendee, A. M.; Rahman, M. M.

2018-03-01

Background/Objectives: The paper discusses about the optimum cutting parameters with coolant techniques condition (1.0 mm nozzle orifice, wet and dry) to optimize surface roughness, temperature and tool wear in the machining process based on the selected setting parameters. The selected cutting parameters for this study were the cutting speed, feed rate, depth of cut and coolant techniques condition. Methods/Statistical Analysis Experiments were conducted and investigated based on Design of Experiment (DOE) with Response Surface Method. The research of the aggressive machining process on aluminum alloy (A319) for automotive applications is an effort to understand the machining concept, which widely used in a variety of manufacturing industries especially in the automotive industry. Findings: The results show that the dominant failure mode is the surface roughness, temperature and tool wear when using 1.0 mm nozzle orifice, increases during machining and also can be alternative minimize built up edge of the A319. The exploration for surface roughness, productivity and the optimization of cutting speed in the technical and commercial aspects of the manufacturing processes of A319 are discussed in automotive components industries for further work Applications/Improvements: The research result also beneficial in minimizing the costs incurred and improving productivity of manufacturing firms. According to the mathematical model and equations, generated by CCD based RSM, experiments were performed and cutting coolant condition technique using size nozzle can reduces tool wear, surface roughness and temperature was obtained. Results have been analyzed and optimization has been carried out for selecting cutting parameters, shows that the effectiveness and efficiency of the system can be identified and helps to solve potential problems.

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.

Nd:YAG Pulsed Laser Assisted Machining of AMS 5708 Waspaloy Alloy

NASA Astrophysics Data System (ADS)

Sharifi, Zahra; Shoja-Razavi, Reza; Vafaei, Reza; Hashemi, Sayed Hamid

2018-03-01

Due to very high strenght, low thermal conductivity, and high work hardening rate, the machinability of nickel-based superalloys is poor at room temperature. Laser-assisted machining (LAM) can provide a better aspect of machining such alloys. Since the wavelength of Nd:YAG laser is about 1/10th of that of CO2 laser, absorption and heating efficiency of Nd:YAG laser is much higher on metals and especially superalloys. Transmission of Nd:YAG laser through fiber optics to the heating point on the workpiece is a simple task during machining. This makes the LAM process more convenient and practical than the CM process. In this study a model is introduced for LAM of waspaloy, and its machinability is evaluated in terms of ease of material removal. Also, a temperature generation model is introduced for the Nd:YAG laser beam. Furthemore, wear behavior of an uncoated tungsten carbide and the formed chips were compared during the LAM and the CM of waspolay. To study the wear mechanism, the worn cutting tool was studied via scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS). The formed chips were also evaluated via SEM and optical microscopy. Based on the results, the optimum LAM conditions were obtained at a cutting speed of 24 m/min and a feed rate of 0.06 mm/rev when a 400 W laser mean power and 80 Hz frequency are applied. Under these conditions, the temperature ahead of the cutting tool edge on the surface of workpiece was estimated to be 524°C. In comparison with CM, a significant improvement in tool wear and a better chip morphology were achieved through LAM, and also specific cutting energy and surface roughness were reduced by 25 and 20%, respectively.

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.

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.

Early experiences in developing and managing the neuroscience gateway.

PubMed

Sivagnanam, Subhashini; Majumdar, Amit; Yoshimoto, Kenneth; Astakhov, Vadim; Bandrowski, Anita; Martone, MaryAnn; Carnevale, Nicholas T

2015-02-01

The last few decades have seen the emergence of computational neuroscience as a mature field where researchers are interested in modeling complex and large neuronal systems and require access to high performance computing machines and associated cyber infrastructure to manage computational workflow and data. The neuronal simulation tools, used in this research field, are also implemented for parallel computers and suitable for high performance computing machines. But using these tools on complex high performance computing machines remains a challenge because of issues with acquiring computer time on these machines located at national supercomputer centers, dealing with complex user interface of these machines, dealing with data management and retrieval. The Neuroscience Gateway is being developed to alleviate and/or hide these barriers to entry for computational neuroscientists. It hides or eliminates, from the point of view of the users, all the administrative and technical barriers and makes parallel neuronal simulation tools easily available and accessible on complex high performance computing machines. It handles the running of jobs and data management and retrieval. This paper shares the early experiences in bringing up this gateway and describes the software architecture it is based on, how it is implemented, and how users can use this for computational neuroscience research using high performance computing at the back end. We also look at parallel scaling of some publicly available neuronal models and analyze the recent usage data of the neuroscience gateway.

Early experiences in developing and managing the neuroscience gateway

PubMed Central

Sivagnanam, Subhashini; Majumdar, Amit; Yoshimoto, Kenneth; Astakhov, Vadim; Bandrowski, Anita; Martone, MaryAnn; Carnevale, Nicholas. T.

2015-01-01

SUMMARY The last few decades have seen the emergence of computational neuroscience as a mature field where researchers are interested in modeling complex and large neuronal systems and require access to high performance computing machines and associated cyber infrastructure to manage computational workflow and data. The neuronal simulation tools, used in this research field, are also implemented for parallel computers and suitable for high performance computing machines. But using these tools on complex high performance computing machines remains a challenge because of issues with acquiring computer time on these machines located at national supercomputer centers, dealing with complex user interface of these machines, dealing with data management and retrieval. The Neuroscience Gateway is being developed to alleviate and/or hide these barriers to entry for computational neuroscientists. It hides or eliminates, from the point of view of the users, all the administrative and technical barriers and makes parallel neuronal simulation tools easily available and accessible on complex high performance computing machines. It handles the running of jobs and data management and retrieval. This paper shares the early experiences in bringing up this gateway and describes the software architecture it is based on, how it is implemented, and how users can use this for computational neuroscience research using high performance computing at the back end. We also look at parallel scaling of some publicly available neuronal models and analyze the recent usage data of the neuroscience gateway. PMID:26523124

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.

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.

Application of Quality Management Tools for Evaluating the Failure Frequency of Cutter-Loader and Plough Mining Systems

NASA Astrophysics Data System (ADS)

Biały, Witold

2017-06-01

Failure frequency in the mining process, with a focus on the mining machine, has been presented and illustrated by the example of two coal-mines. Two mining systems have been subjected to analysis: a cutter-loader and a plough system. In order to reduce costs generated by failures, maintenance teams should regularly make sure that the machines are used and operated in a rational and effective way. Such activities will allow downtimes to be reduced, and, in consequence, will increase the effectiveness of a mining plant. The evaluation of mining machines' failure frequency contained in this study has been based on one of the traditional quality management tools - the Pareto chart.

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 force, temperature and surface roughness data is developed and used to study the deformation mechanisms of porous tungsten under different machining conditions. It is found that when hmax = hc, ductile mode machining of otherwise highly brittle porous tungsten is possible. The value of hc is approximately the same as the average ligament size of the 80% density porous tungsten workpiece.

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

Exploring the influence of constitutive models and associated parameters for the orthogonal machining of Ti6Al4V

NASA Astrophysics Data System (ADS)

Pervaiz, S.; Anwar, S.; Kannan, S.; Almarfadi, A.

2018-04-01

Ti6Al4V is known as difficult-to-cut material due to its inherent properties such as high hot hardness, low thermal conductivity and high chemical reactivity. Though, Ti6Al4V is utilized by industrial sectors such as aeronautics, energy generation, petrochemical and bio-medical etc. For the metal cutting community, competent and cost-effective machining of Ti6Al4V is a challenging task. To optimize cost and machining performance for the machining of Ti6Al4V, finite element based cutting simulation can be a very useful tool. The aim of this paper is to develop a finite element machining model for the simulation of Ti6Al4V machining process. The study incorporates material constitutive models namely Power Law (PL) and Johnson – Cook (JC) material models to mimic the mechanical behaviour of Ti6Al4V. The study investigates cutting temperatures, cutting forces, stresses, and plastic strains with respect to different PL and JC material models with associated parameters. In addition, the numerical study also integrates different cutting tool rake angles in the machining simulations. The simulated results will be beneficial to draw conclusions for improving the overall machining performance of Ti6Al4V.

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.

Tool Efficiency Analysis model research in SEMI industry

NASA Astrophysics Data System (ADS)

Lei, Ma; Nana, Zhang; Zhongqiu, Zhang

2018-06-01

One of the key goals in SEMI industry is to improve equipment through put and ensure equipment production efficiency maximization. This paper is based on SEMI standards in semiconductor equipment control, defines the transaction rules between different tool states, and presents a TEA system model which is to analysis tool performance automatically based on finite state machine. The system was applied to fab tools and verified its effectiveness successfully, and obtained the parameter values used to measure the equipment performance, also including the advices of improvement.

The optimization study on the tool wear of carbide cutting tool during milling Carbon Fibre Reinforced (CFRP) using Response Surface Methodology (RSM)

NASA Astrophysics Data System (ADS)

Nor Khairusshima, M. K.; Hafiz Zakwan, B. Muhammad; Suhaily, M.; Sharifah, I. S. S.; Shaffiar, N. M.; Rashid, M. A. N.

2018-01-01

Carbon Fibre Reinforced Plastic (CFRP) composite has become one of famous materials in industry, such as automotive, aeronautics, aerospace and aircraft. CFRP is attractive due to its properties, which promising better strength and high specification of mechanical properties other than its high resistance to corrosion. Other than being abrasive material due to the carbon nature, CFRP is an anisotropic material, which the knowledge of machining metal and steel cannot be applied during machining CFRP. The improper technique and parameters used to machine CFRP may result in high tool wear. This paper is to study the tool wear of 8 mm diameter carbide cutting tool during milling CFRP. To predict the suitable cutting parameters within range of 3500-6220 (rev/min), 200-245 (mm/min), and 0.4-1.8 (mm) for cutting speed, speed, feed rate and depth of cut respectively, which produce optimized result (less tool wear), Response Surface Methodology (RSM) has been used. Based on the developed mathematical model, feed rate was identified as the primary significant item that influenced tool wear. The optimized cutting parameters are cutting speed, feed and depth of cut of 3500 rev/min, 200 mm/min and 0.5 mm, respectively, with tool wear of 0.0267 mm. It is also can be observed that as the cutting speed and feed rate increased the tool wear is increasing.

Springback effects during single point incremental forming: Optimization of the tool path

NASA Astrophysics Data System (ADS)

Giraud-Moreau, Laurence; Belchior, Jérémy; Lafon, Pascal; Lotoing, Lionel; Cherouat, Abel; Courtielle, Eric; Guines, Dominique; Maurine, Patrick

2018-05-01

Incremental sheet forming is an emerging process to manufacture sheet metal parts. This process is more flexible than conventional one and well suited for small batch production or prototyping. During the process, the sheet metal blank is clamped by a blank-holder and a small-size smooth-end hemispherical tool moves along a user-specified path to deform the sheet incrementally. Classical three-axis CNC milling machines, dedicated structure or serial robots can be used to perform the forming operation. Whatever the considered machine, large deviations between the theoretical shape and the real shape can be observed after the part unclamping. These deviations are due to both the lack of stiffness of the machine and residual stresses in the part at the end of the forming stage. In this paper, an optimization strategy of the tool path is proposed in order to minimize the elastic springback induced by residual stresses after unclamping. A finite element model of the SPIF process allowing the shape prediction of the formed part with a good accuracy is defined. This model, based on appropriated assumptions, leads to calculation times which remain compatible with an optimization procedure. The proposed optimization method is based on an iterative correction of the tool path. The efficiency of the method is shown by an improvement of the final shape.

Physical Modeling of Contact Processes on the Cutting Tools Surfaces of STM When Turning

NASA Astrophysics Data System (ADS)

Belozerov, V. A.; Uteshev, M. H.

2016-08-01

This article describes how to create an optimization model of the process of fine turning of superalloys and steel tools from STM on CNC machines, flexible manufacturing units (GPM), machining centers. Creation of the optimization model allows you to link (unite) contact processes simultaneously on the front and back surfaces of the tool from STM to manage contact processes and the dynamic strength of the cutting tool at the top of the STM. Established optimization model of management of the dynamic strength of the incisors of the STM in the process of fine turning is based on a previously developed thermomechanical (physical, heat) model, which allows the system thermomechanical approach to choosing brands STM (domestic and foreign) for cutting tools from STM designed for fine turning of heat resistant alloys and steels.

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

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

Virtual Reality Simulations and Animations in a Web-Based Interactive Manufacturing Engineering Module

ERIC Educational Resources Information Center

Ong, S. K.; Mannan, M. A.

2004-01-01

This paper presents a web-based interactive teaching package that provides a comprehensive and conducive yet dynamic and interactive environment for a module on automated machine tools in the Manufacturing Division at the National University of Singapore. The use of Internet technologies in this teaching tool makes it possible to conjure…

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…

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

Direct Digital Manufacturing of Integrated Naval Systems Using Ultrasonic Consolidation, Support Material Deposition and Direct Write Technologies

DTIC Science & Technology

2012-02-17

tool should be combined with a user-friendly Windows-based software interface that utilizes the best practices for process planning developed by us and...best practices developed through this project, resulting in the commercial availability of machines for the Navy and others. These machines will...research 2011 Outstanding Paper Award, VRAP 2011, for paper "Some Studies on Dislocation Density based Finite Element Modeling of Ultrasonic

Optimization of Milling Parameters Employing Desirability Functions

NASA Astrophysics Data System (ADS)

Ribeiro, J. L. S.; Rubio, J. C. Campos; Abrão, A. M.

2011-01-01

The principal aim of this paper is to investigate the influence of tool material (one cermet and two coated carbide grades), cutting speed and feed rate on the machinability of hardened AISI H13 hot work steel, in order to identify the cutting conditions which lead to optimal performance. A multiple response optimization procedure based on tool life, surface roughness, milling forces and the machining time (required to produce a sample cavity) was employed. The results indicated that the TiCN-TiN coated carbide and cermet presented similar results concerning the global optimum values for cutting speed and feed rate per tooth, outperforming the TiN-TiCN-Al2O3 coated carbide tool.

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.

A new digitized reverse correction method for hypoid gears based on a one-dimensional probe

NASA Astrophysics Data System (ADS)

Li, Tianxing; Li, Jubo; Deng, Xiaozhong; Yang, Jianjun; Li, Genggeng; Ma, Wensuo

2017-12-01

In order to improve the tooth surface geometric accuracy and transmission quality of hypoid gears, a new digitized reverse correction method is proposed based on the measurement data from a one-dimensional probe. The minimization of tooth surface geometrical deviations is realized from the perspective of mathematical analysis and reverse engineering. Combining the analysis of complex tooth surface generation principles and the measurement mechanism of one-dimensional probes, the mathematical relationship between the theoretical designed tooth surface, the actual machined tooth surface and the deviation tooth surface is established, the mapping relation between machine-tool settings and tooth surface deviations is derived, and the essential connection between the accurate calculation of tooth surface deviations and the reverse correction method of machine-tool settings is revealed. Furthermore, a reverse correction model of machine-tool settings is built, a reverse correction strategy is planned, and the minimization of tooth surface deviations is achieved by means of the method of numerical iterative reverse solution. On this basis, a digitized reverse correction system for hypoid gears is developed by the organic combination of numerical control generation, accurate measurement, computer numerical processing, and digitized correction. Finally, the correctness and practicability of the digitized reverse correction method are proved through a reverse correction experiment. The experimental results show that the tooth surface geometric deviations meet the engineering requirements after two trial cuts and one correction.

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.

THE COMPUTER CONCEPT OF SELF-INSTRUCTIONAL DEVICES.

ERIC Educational Resources Information Center

SILBERMAN, HARRY F.

THE COMPUTER SYSTEM CONCEPT WILL BE DEVELOPED IN TWO WAYS--FIRST, A DESCRIPTION WILL BE MADE OF THE SMALL COMPUTER-BASED TEACHING MACHINE WHICH IS BEING USED AS A RESEARCH TOOL, SECOND, A DESCRIPTION WILL BE MADE OF THE LARGE COMPUTER LABORATORY FOR AUTOMATED SCHOOL SYSTEMS WHICH ARE BEING DEVELOPED. THE FIRST MACHINE CONSISTS OF THREE ELEMENTS--…

Effect of the Machining Processes on Low Cycle Fatigue Behavior of a Powder Metallurgy Disk

NASA Technical Reports Server (NTRS)

Telesman, J.; Kantzos, P.; Gabb, T. P.; Ghosn, L. J.

2010-01-01

A study has been performed to investigate the effect of various machining processes on fatigue life of configured low cycle fatigue specimens machined out of a NASA developed LSHR P/M nickel based disk alloy. Two types of configured specimen geometries were employed in the study. To evaluate a broach machining processes a double notch geometry was used with both notches machined using broach tooling. EDM machined notched specimens of the same configuration were tested for comparison purposes. Honing finishing process was evaluated by using a center hole specimen geometry. Comparison testing was again done using EDM machined specimens of the same geometry. The effect of these machining processes on the resulting surface roughness, residual stress distribution and microstructural damage were characterized and used in attempt to explain the low cycle fatigue results.

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

ControlShell: A real-time software framework

NASA Technical Reports Server (NTRS)

Schneider, Stanley A.; Chen, Vincent W.; Pardo-Castellote, Gerardo

1994-01-01

The ControlShell system is a programming environment that enables the development and implementation of complex real-time software. It includes many building tools for complex systems, such as a graphical finite state machine (FSM) tool to provide strategic control. ControlShell has a component-based design, providing interface definitions and mechanisms for building real-time code modules along with providing basic data management. Some of the system-building tools incorporated in ControlShell are a graphical data flow editor, a component data requirement editor, and a state-machine editor. It also includes a distributed data flow package, an execution configuration manager, a matrix package, and an object database and dynamic binding facility. This paper presents an overview of ControlShell's architecture and examines the functions of several of its tools.

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.

Apparatus for electrical-assisted incremental forming and process thereof

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

Roth, John; Cao, Jian

A process and apparatus for forming a sheet metal component using an electric current passing through the component. The process can include providing an incremental forming machine, the machine having at least one arcuate tipped tool and at least electrode spaced a predetermined distance from the arcuate tipped tool. The machine is operable to perform a plurality of incremental deformations on the sheet metal component using the arcuate tipped tool. The machine is also operable to apply an electric direct current through the electrode into the sheet metal component at the predetermined distance from the arcuate tipped tool while themore » machine is forming the sheet metal component.« less

Migrating EO/IR sensors to cloud-based infrastructure as service architectures

NASA Astrophysics Data System (ADS)

Berglie, Stephen T.; Webster, Steven; May, Christopher M.

2014-06-01

The Night Vision Image Generator (NVIG), a product of US Army RDECOM CERDEC NVESD, is a visualization tool used widely throughout Army simulation environments to provide fully attributed synthesized, full motion video using physics-based sensor and environmental effects. The NVIG relies heavily on contemporary hardware-based acceleration and GPU processing techniques, which push the envelope of both enterprise and commodity-level hypervisor support for providing virtual machines with direct access to hardware resources. The NVIG has successfully been integrated into fully virtual environments where system architectures leverage cloudbased technologies to various extents in order to streamline infrastructure and service management. This paper details the challenges presented to engineers seeking to migrate GPU-bound processes, such as the NVIG, to virtual machines and, ultimately, Cloud-Based IAS architectures. In addition, it presents the path that led to success for the NVIG. A brief overview of Cloud-Based infrastructure management tool sets is provided, and several virtual desktop solutions are outlined. A discrimination is made between general purpose virtual desktop technologies compared to technologies that expose GPU-specific capabilities, including direct rendering and hard ware-based video encoding. Candidate hypervisor/virtual machine configurations that nominally satisfy the virtualized hardware-level GPU requirements of the NVIG are presented , and each is subsequently reviewed in light of its implications on higher-level Cloud management techniques. Implementation details are included from the hardware level, through the operating system, to the 3D graphics APls required by the NVIG and similar GPU-bound tools.

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.

Reversible micromachining locator

DOEpatents

Salzer, Leander J.; Foreman, Larry R.

2002-01-01

A locator with a part support is used to hold a part onto the kinematic mount of a tooling machine so that the part can be held in or replaced in exactly the same position relative to the cutting tool for machining different surfaces of the part or for performing different machining operations on the same or different surfaces of the part. The locator has disposed therein a plurality of steel balls placed at equidistant positions around the planar surface of the locator and the kinematic mount has a plurality of magnets which alternate with grooves which accommodate the portions of the steel balls projecting from the locator. The part support holds the part to be machined securely in place in the locator. The locator can be easily detached from the kinematic mount, turned over, and replaced onto the same kinematic mount or another kinematic mount on another tooling machine without removing the part to be machined from the locator so that there is no need to touch or reposition the part within the locator, thereby assuring exact replication of the position of the part in relation to the cutting tool on the tooling machine for each machining operation on the part.

Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta

2008-01-01

Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…

Experimental research of kinetic and dynamic characteristics of temperature movements of machines

NASA Astrophysics Data System (ADS)

Parfenov, I. V.; Polyakov, A. N.

2018-03-01

Nowadays, the urgency of informational support of machines at different stages of their life cycle is increasing in the form of various experimental characteristics that determine the criteria for working capacity. The effectiveness of forming the base of experimental characteristics of machines is related directly to the duration of their field tests. In this research, the authors consider a new technique that allows reducing the duration of full-scale testing of machines by 30%. To this end, three new indicator coefficients were calculated in real time to determine the moments corresponding to the characteristic points. In the work, new terms for thermal characteristics of machine tools are introduced: kinetic and dynamic characteristics of the temperature movements of the machine. This allow taking into account not only the experimental values for the temperature displacements of the elements of the carrier system of the machine, but also their derivatives up to the third order, inclusively. The work is based on experimental data obtained in the course of full-scale thermal tests of a drilling-milling and boring CNC machine.

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,…

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.

Experimental and numerical investigations on the temperature distribution in PVD AlTiN coated and uncoated Al2O3/TiCN mixed ceramic cutting tools in hard turning of AISI 52100 steel

NASA Astrophysics Data System (ADS)

Sateesh Kumar, Ch; Patel, Saroj Kumar; Das, Anshuman

2018-03-01

Temperature generation in cutting tools is one of the major causes of tool failure especially during hard machining where machining forces are quite high resulting in elevated temperatures. Thus, the present work investigates the temperature generation during hard machining of AISI 52100 steel (62 HRC hardness) with uncoated and PVD AlTiN coated Al2O3/TiCN mixed ceramic cutting tools. The experiments were performed on a heavy duty lathe machine with both coated and uncoated cutting tools under dry cutting environment. The temperature of the cutting zone was measured using an infrared thermometer and a finite element model has been adopted to predict the temperature distribution in cutting tools during machining for comparative assessment with the measured temperature. The experimental and numerical results revealed a significant reduction of cutting zone temperature during machining with PVD AlTiN coated cutting tools when compared to uncoated cutting tools during each experimental run. The main reason for decrease in temperature for AlTiN coated tools is the lower coefficient of friction offered by the coating material which allows the free flow of the chips on the rake surface when compared with uncoated cutting tools. Further, the superior wear behaviour of AlTiN coating resulted in reduction of cutting temperature.

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.

Tool geometry and damage mechanisms influencing CNC turning efficiency of Ti6Al4V

NASA Astrophysics Data System (ADS)

Suresh, Sangeeth; Hamid, Darulihsan Abdul; Yazid, M. Z. A.; Nasuha, Nurdiyanah; Ain, Siti Nurul

2017-12-01

Ti6Al4V or Grade 5 titanium alloy is widely used in the aerospace, medical, automotive and fabrication industries, due to its distinctive combination of mechanical and physical properties. Ti6Al4V has always been perverse during its machining, strangely due to the same mix of properties mentioned earlier. Ti6Al4V machining has resulted in shorter cutting tool life which has led to objectionable surface integrity and rapid failure of the parts machined. However, the proven functional relevance of this material has prompted extensive research in the optimization of machine parameters and cutting tool characteristics. Cutting tool geometry plays a vital role in ensuring dimensional and geometric accuracy in machined parts. In this study, an experimental investigation is actualized to optimize the nose radius and relief angles of the cutting tools and their interaction to different levels of machining parameters. Low elastic modulus and thermal conductivity of Ti6Al4V contribute to the rapid tool damage. The impact of these properties over the tool tips damage is studied. An experimental design approach is utilized in the CNC turning process of Ti6Al4V to statistically analyze and propose optimum levels of input parameters to lengthen the tool life and enhance surface characteristics of the machined parts. A greater tool nose radius with a straight flank, combined with low feed rates have resulted in a desirable surface integrity. The presence of relief angle has proven to aggravate tool damage and also dimensional instability in the CNC turning of Ti6Al4V.

Machinability of lithium disilicate glass ceramic in in vitro dental diamond bur adjusting process.

PubMed

Song, Xiao-Fei; Ren, Hai-Tao; Yin, Ling

2016-01-01

Esthetic high-strength lithium disilicate glass ceramics (LDGC) are used for monolithic crowns and bridges produced in dental CAD/CAM and oral adjusting processes, which machinability affects the restorative quality. A machinability study has been made in the simulated oral clinical machining of LDGC with a dental handpiece and diamond burs, regarding the diamond tool wear and chip control, machining forces and energy, surface finish and integrity. Machining forces, speeds and energy in in vitro dental adjusting of LDGC were measured by a high-speed data acquisition and force sensor system. Machined LDGC surfaces were assessed using three-dimensional non-contact chromatic confocal optical profilometry and scanning electron microscopy (SEM). Diamond bur morphology and LDGC chip shapes were also examined using SEM. Minimum tool wear but significant LDGC chip accumulations were found. Machining forces and energy significantly depended on machining conditions (p<0.05) and were significantly higher than other glass ceramics (p<0.05). Machining speeds dropped more rapidly with increased removal rates than other glass ceramics (p<0.05). Two material machinability indices associated with the hardness, Young's modulus and fracture toughness were derived based on the normal force-removal rate relations, which ranked LDGC the most difficult to machine among glass ceramics. Surface roughness for machined LDGC was comparable for other glass ceramics. The removal mechanisms of LDGC were dominated by penetration-induced brittle fracture and shear-induced plastic deformation. Unlike most other glass ceramics, distinct intergranular and transgranular fractures of lithium disilicate crystals were found in LDGC. This research provides the fundamental data for dental clinicians on the machinability of LDGC in intraoral adjustments. Copyright © 2015 Elsevier Ltd. All rights reserved.

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...

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.

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.

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.

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.

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.

Personal manufacturing systems

NASA Astrophysics Data System (ADS)

Bailey, P.

1992-04-01

Personal Manufacturing Systems are the missing link in the automation of the design-to- manufacture process. A PMS will act as a CAD peripheral, closing the loop around the designer enabling him to directly produce models, short production runs or soft tooling with as little fuss as he might otherwise plot a drawing. Whereas conventional 5-axis CNC machines are based on orthogonal axes and simple incremental movements, the PMS is based on a geodetic structure and complex co-ordinated 'spline' movements. The software employs a novel 3D pixel technique for give itself 'spatial awareness' and an expert system to determine the optimum machining conditions. A completely automatic machining strategy can then be determined.

Impact of oscillations of shafts on machining accuracy using non-stationary machines

NASA Astrophysics Data System (ADS)

Fedorenko, M. A.; Bondarenko, J. A.; Pogonin, A. A.

2018-03-01

The solution of the problem of restoring parts and units of equipment of the large mass and size is possible on the basis of the development of the research base, including the development of models and theoretical relations, revealing complex reasons for causes of damage and equipment failure. This allows one to develop new effective technologies of maintenance and repair, implementation of which ensures the efficiency and durability of the machines. The development of new forms of technical maintenance and repair of equipment, based on a systematic evaluation of its technical condition with the help of modern diagnostic tools can significantly reduce the duration of the downtime.

On-line Monitoring for Cutting Tool Wear Condition Based on the Parameters

NASA Astrophysics Data System (ADS)

Han, Fenghua; Xie, Feng

2017-07-01

In the process of cutting tools, it is very important to monitor the working state of the tools. On the basis of acceleration signal acquisition under the constant speed, time domain and frequency domain analysis of relevant indicators monitor the online of tool wear condition. The analysis results show that the method can effectively judge the tool wear condition in the process of machining. It has certain application value.

The IHMC CmapTools software in research and education: a multi-level use case in Space Meteorology

NASA Astrophysics Data System (ADS)

Messerotti, Mauro

2010-05-01

The IHMC (Institute for Human and Machine Cognition, Florida University System, USA) CmapTools software is a powerful multi-platform tool for knowledge modelling in graphical form based on concept maps. In this work we present its application for the high-level development of a set of multi-level concept maps in the framework of Space Meteorology to act as the kernel of a space meteorology domain ontology. This is an example of a research use case, as a domain ontology coded in machine-readable form via e.g. OWL (Web Ontology Language) is suitable to be an active layer of any knowledge management system embedded in a Virtual Observatory (VO). Apart from being manageable at machine level, concept maps developed via CmapTools are intrinsically human-readable and can embed hyperlinks and objects of many kinds. Therefore they are suitable to be published on the web: the coded knowledge can be exploited for educational purposes by the students and the public, as the level of information can be naturally organized among linked concept maps in progressively increasing complexity levels. Hence CmapTools and its advanced version COE (Concept-map Ontology Editor) represent effective and user-friendly software tools for high-level knowledge represention in research and education.

Productivity improvement through cycle time analysis

NASA Astrophysics Data System (ADS)

Bonal, Javier; Rios, Luis; Ortega, Carlos; Aparicio, Santiago; Fernandez, Manuel; Rosendo, Maria; Sanchez, Alejandro; Malvar, Sergio

1996-09-01

A cycle time (CT) reduction methodology has been developed in the Lucent Technology facility (former AT&T) in Madrid, Spain. It is based on a comparison of the contribution of each process step in each technology with a target generated by a cycle time model. These targeted cycle times are obtained using capacity data of the machines processing those steps, queuing theory and theory of constrains (TOC) principles (buffers to protect bottleneck and low cycle time/inventory everywhere else). Overall efficiency equipment (OEE) like analysis is done in the machine groups with major differences between their target cycle time and real values. Comparisons between the current value of the parameters that command their capacity (process times, availability, idles, reworks, etc.) and the engineering standards are done to detect the cause of exceeding their contribution to the cycle time. Several friendly and graphical tools have been developed to track and analyze those capacity parameters. Specially important have showed to be two tools: ASAP (analysis of scheduling, arrivals and performance) and performer which analyzes interrelation problems among machines procedures and direct labor. The performer is designed for a detailed and daily analysis of an isolate machine. The extensive use of this tool by the whole labor force has demonstrated impressive results in the elimination of multiple small inefficiencies with a direct positive implications on OEE. As for ASAP, it shows the lot in process/queue for different machines at the same time. ASAP is a powerful tool to analyze the product flow management and the assigned capacity for interdependent operations like the cleaning and the oxidation/diffusion. Additional tools have been developed to track, analyze and improve the process times and the availability.

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.

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.

Analysis of machining accuracy during free form surface milling simulation for different milling strategies

NASA Astrophysics Data System (ADS)

Matras, A.; Kowalczyk, R.

2014-11-01

The analysis results of machining accuracy after the free form surface milling simulations (based on machining EN AW- 7075 alloys) for different machining strategies (Level Z, Radial, Square, Circular) are presented in the work. Particular milling simulations were performed using CAD/CAM Esprit software. The accuracy of obtained allowance is defined as a difference between the theoretical surface of work piece element (the surface designed in CAD software) and the machined surface after a milling simulation. The difference between two surfaces describes a value of roughness, which is as the result of tool shape mapping on the machined surface. Accuracy of the left allowance notifies in direct way a surface quality after the finish machining. Described methodology of usage CAD/CAM software can to let improve a time design of machining process for a free form surface milling by a 5-axis CNC milling machine with omitting to perform the item on a milling machine in order to measure the machining accuracy for the selected strategies and cutting data.

Modeling the milling tool wear by using an evolutionary SVM-based model from milling runs experimental data

NASA Astrophysics Data System (ADS)

Nieto, Paulino José García; García-Gonzalo, Esperanza; Vilán, José Antonio Vilán; Robleda, Abraham Segade

2015-12-01

The main aim of this research work is to build a new practical hybrid regression model to predict the milling tool wear in a regular cut as well as entry cut and exit cut of a milling tool. The model was based on Particle Swarm Optimization (PSO) in combination with support vector machines (SVMs). This optimization mechanism involved kernel parameter setting in the SVM training procedure, which significantly influences the regression accuracy. Bearing this in mind, a PSO-SVM-based model, which is based on the statistical learning theory, was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. To accomplish the objective of this study, the experimental dataset represents experiments from runs on a milling machine under various operating conditions. In this way, data sampled by three different types of sensors (acoustic emission sensor, vibration sensor and current sensor) were acquired at several positions. A second aim is to determine the factors with the greatest bearing on the milling tool flank wear with a view to proposing milling machine's improvements. Firstly, this hybrid PSO-SVM-based regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the flank wear (output variable) and input variables (time, depth of cut, feed, etc.). Indeed, regression with optimal hyperparameters was performed and a determination coefficient of 0.95 was obtained. The agreement of this model with experimental data confirmed its good performance. Secondly, the main advantages of this PSO-SVM-based model are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, the main conclusions of this study are exposed.

Experimental Investigation Nano Particles Influence in NPMEDM to Machine Inconel 800 with Electrolyte Copper Electrode

NASA Astrophysics Data System (ADS)

Karunakaran, K.; Chandrasekaran, M.

2017-05-01

The recent technology of machining hard materials is Powder mix dielectric electrical Discharge Machining (PMEDM). This research investigates nano sized (about 5Nm) powders influence in machining Inconel 800 nickel based super alloy. This work is motivated for a practical need for a manufacturing industry, which processes various kinds of jobs of Inconel 800 material. The conventional EDM machining also considered for investigation for the measure of Nano powders performances. The aluminum, silicon and multi walled Carbon Nano tubes powders were considered in this investigation along with pulse on time, pulse of time and input current to analyze and optimize the responses of Material Removal Rate, Tool Wear Rate and surface roughness. The Taguchi general Full Factorial Design was used to design the experiments. The most advance equipments employed in conducting experiments and measuring equipments to improve the accuracy of the result. The MWCNT powder mix was out performs than other powders which reduce 22% to 50% of the tool wear rate, gives the surface roughness reduction from 29.62% to 41.64% and improved MRR 42.91% to 53.51% than conventional EDM.

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.

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.

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.

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.

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

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.

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.

A machine vision system for micro-EDM based on linux

NASA Astrophysics Data System (ADS)

Guo, Rui; Zhao, Wansheng; Li, Gang; Li, Zhiyong; Zhang, Yong

2006-11-01

Due to the high precision and good surface quality that it can give, Electrical Discharge Machining (EDM) is potentially an important process for the fabrication of micro-tools and micro-components. However, a number of issues remain unsolved before micro-EDM becomes a reliable process with repeatable results. To deal with the difficulties in micro electrodes on-line fabrication and tool wear compensation, a micro-EDM machine vision system is developed with a Charge Coupled Device (CCD) camera, with an optical resolution of 1.61μm and an overall magnification of 113~729. Based on the Linux operating system, an image capturing program is developed with the V4L2 API, and an image processing program is exploited by using OpenCV. The contour of micro electrodes can be extracted by means of the Canny edge detector. Through the system calibration, the micro electrodes diameter can be measured on-line. Experiments have been carried out to prove its performance, and the reasons of measurement error are also analyzed.

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

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.

Tool wear modeling using abductive networks

NASA Astrophysics Data System (ADS)

Masory, Oren

1992-09-01

A tool wear model based on Abductive Networks, which consists of a network of `polynomial' nodes, is described. The model relates the cutting parameters, components of the cutting force, and machining time to flank wear. Thus real time measurements of the cutting force can be used to monitor the machining process. The model is obtained by a training process in which the connectivity between the network's nodes and the polynomial coefficients of each node are determined by optimizing a performance criteria. Actual wear measurements of coated and uncoated carbide inserts were used for training and evaluating the established model.

Results of Investigative Tests of Gas Turbine Engine Compressor Blades Obtained by Electrochemical Machining

NASA Astrophysics Data System (ADS)

Kozhina, T. D.; Kurochkin, A. V.

2016-04-01

The paper highlights results of the investigative tests of GTE compressor Ti-alloy blades obtained by the method of electrochemical machining with oscillating tool-electrodes, carried out in order to define the optimal parameters of the ECM process providing attainment of specified blade quality parameters given in the design documentation, while providing maximal performance. The new technological methods suggested based on the results of the tests; in particular application of vibrating tool-electrodes and employment of locating elements made of high-strength materials, significantly extend the capabilities of this method.

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

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.

Automatic welding detection by an intelligent tool pipe inspection

NASA Astrophysics Data System (ADS)

Arizmendi, C. J.; Garcia, W. L.; Quintero, M. A.

2015-07-01

This work provide a model based on machine learning techniques in welds recognition, based on signals obtained through in-line inspection tool called “smart pig” in Oil and Gas pipelines. The model uses a signal noise reduction phase by means of pre-processing algorithms and attribute-selection techniques. The noise reduction techniques were selected after a literature review and testing with survey data. Subsequently, the model was trained using recognition and classification algorithms, specifically artificial neural networks and support vector machines. Finally, the trained model was validated with different data sets and the performance was measured with cross validation and ROC analysis. The results show that is possible to identify welding automatically with an efficiency between 90 and 98 percent.

Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

PubMed

Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

2011-05-15

There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

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.

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.

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…

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.

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

Saleh, Z; Tang, X; Song, Y

Purpose: To investigate the long term stability and viability of using EPID-based daily output QA via in-house and vendor driven protocol, to replace conventional QA tools and improve QA efficiency. Methods: Two Varian TrueBeam machines (TB1&TB2) equipped with electronic portal imaging devices (EPID) were employed in this study. Both machines were calibrated per TG-51 and used clinically since Oct 2014. Daily output measurement for 6/15 MV beams were obtained using SunNuclear DailyQA3 device as part of morning QA. In addition, in-house protocol was implemented for EPID output measurement (10×10 cm fields, 100 MU, 100cm SID, output defined over an ROImore » of 2×2 cm around central axis). Moreover, the Varian Machine Performance Check (MPC) was used on both machines to measure machine output. The EPID and DailyQA3 based measurements of the relative machine output were compared and cross-correlated with monthly machine output as measured by an A12 Exradin 0.65cc Ion Chamber (IC) serving as ground truth. The results were correlated using Pearson test. Results: The correlations among DailyQA3, in-house EPID and Varian MPC output measurements, with the IC for 6/15 MV were similar for TB1 (0.83–0.95) and TB2 (0.55–0.67). The machine output for the 6/15MV beams on both machines showed a similar trend, namely an increase over time as indicated by all measurements, requiring a machine recalibration after 6 months. This drift is due to a known issue with pressurized monitor chamber which tends to leak over time. MPC failed occasionally but passed when repeated. Conclusion: The results indicate that the use of EPID for daily output measurements has the potential to become a viable and efficient tool for daily routine LINAC QA, thus eliminating weather (T,P) and human setup variability and increasing efficiency of the QA process.« less

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

[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.

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.

Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

PubMed

Grouin, Cyril; Zweigenbaum, Pierre

2013-01-01

In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

Development of a QFD-based expert system for CNC turning centre selection

NASA Astrophysics Data System (ADS)

Prasad, Kanika; Chakraborty, Shankar

2015-12-01

Computer numerical control (CNC) machine tools are automated devices capable of generating complicated and intricate product shapes in shorter time. Selection of the best CNC machine tool is a critical, complex and time-consuming task due to availability of a wide range of alternatives and conflicting nature of several evaluation criteria. Although, the past researchers had attempted to select the appropriate machining centres using different knowledge-based systems, mathematical models and multi-criteria decision-making methods, none of those approaches has given due importance to the voice of customers. The aforesaid limitation can be overcome using quality function deployment (QFD) technique, which is a systematic approach for integrating customers' needs and designing the product to meet those needs first time and every time. In this paper, the adopted QFD-based methodology helps in selecting CNC turning centres for a manufacturing organization, providing due importance to the voice of customers to meet their requirements. An expert system based on QFD technique is developed in Visual BASIC 6.0 to automate the CNC turning centre selection procedure for different production plans. Three illustrative examples are demonstrated to explain the real-time applicability of the developed expert system.

Python Spectral Analysis Tool (PySAT) for Preprocessing, Multivariate Analysis, and Machine Learning with Point Spectra

NASA Astrophysics Data System (ADS)

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

2017-06-01

We present a Python-based library and graphical interface for the analysis of point spectra. The tool is being developed with a focus on methods used for ChemCam data, but is flexible enough to handle spectra from other instruments.

A collaborative framework for Distributed Privacy-Preserving Support Vector Machine learning.

PubMed

Que, Jialan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

A Support Vector Machine (SVM) is a popular tool for decision support. The traditional way to build an SVM model is to estimate parameters based on a centralized repository of data. However, in the field of biomedicine, patient data are sometimes stored in local repositories or institutions where they were collected, and may not be easily shared due to privacy concerns. This creates a substantial barrier for researchers to effectively learn from the distributed data using machine learning tools like SVMs. To overcome this difficulty and promote efficient information exchange without sharing sensitive raw data, we developed a Distributed Privacy Preserving Support Vector Machine (DPP-SVM). The DPP-SVM enables privacy-preserving collaborative learning, in which a trusted server integrates "privacy-insensitive" intermediary results. The globally learned model is guaranteed to be exactly the same as learned from combined data. We also provide a free web-service (http://privacy.ucsd.edu:8080/ppsvm/) for multiple participants to collaborate and complete the SVM-learning task in an efficient and privacy-preserving manner.

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.

The technique of entropy optimization in motor current signature analysis and its application in the fault diagnosis of gear transmission

NASA Astrophysics Data System (ADS)

Chen, Xiaoguang; Liang, Lin; Liu, Fei; Xu, Guanghua; Luo, Ailing; Zhang, Sicong

2012-05-01

Nowadays, Motor Current Signature Analysis (MCSA) is widely used in the fault diagnosis and condition monitoring of machine tools. However, although the current signal has lower SNR (Signal Noise Ratio), it is difficult to identify the feature frequencies of machine tools from complex current spectrum that the feature frequencies are often dense and overlapping by traditional signal processing method such as FFT transformation. With the study in the Motor Current Signature Analysis (MCSA), it is found that the entropy is of importance for frequency identification, which is associated with the probability distribution of any random variable. Therefore, it plays an important role in the signal processing. In order to solve the problem that the feature frequencies are difficult to be identified, an entropy optimization technique based on motor current signal is presented in this paper for extracting the typical feature frequencies of machine tools which can effectively suppress the disturbances. Some simulated current signals were made by MATLAB, and a current signal was obtained from a complex gearbox of an iron works made in Luxembourg. In diagnosis the MCSA is combined with entropy optimization. Both simulated and experimental results show that this technique is efficient, accurate and reliable enough to extract the feature frequencies of current signal, which provides a new strategy for the fault diagnosis and the condition monitoring of machine tools.

Impact resistance of guards on grinding machines.

PubMed

Mewes, Detlef; Mewes, Olaf; Herbst, Peter

2011-01-01

Guards on machine tools are meant to protect persons from injuries caused by parts ejected with high kinetic energy from the machine's working zone. With respect to stationary grinding machines, Standard No. EN 13218:2002, therefore, specifies minimum wall thicknesses for guards. These values are mainly based on estimations and experience instead of systematic experimental investigations. This paper shows to what extent simple impact tests with standardizable projectiles can be used as basis for the evaluation of the impact resistance of guards, provided that not only the kinetic energy of the projectiles used but also, among others, their geometry corresponds to the abrasive product fragments to be expected.

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.

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.

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.

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.

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…

JPRS Report, China.

DTIC Science & Technology

1989-01-30

absolutely forbid the dealing of retaliatory blows to those of the masses who give their opinions. Fifth, on the basis of their analyses they pass on...Timber Artificial Board Cement Plate Glass Power Equipment Machine Tool Precision Machine Tool Large Machine Tool Automobile Truck Tractor Small...the State Bureau of Building Materials Industry said that the industry must manufacture more varieties of high quality cement, glass , pottery, and

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.

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.

Development of a computer-based clinical decision support tool for selecting appropriate rehabilitation interventions for injured workers.

PubMed

Gross, Douglas P; Zhang, Jing; Steenstra, Ivan; Barnsley, Susan; Haws, Calvin; Amell, Tyler; McIntosh, Greg; Cooper, Juliette; Zaiane, Osmar

2013-12-01

To develop a classification algorithm and accompanying computer-based clinical decision support tool to help categorize injured workers toward optimal rehabilitation interventions based on unique worker characteristics. Population-based historical cohort design. Data were extracted from a Canadian provincial workers' compensation database on all claimants undergoing work assessment between December 2009 and January 2011. Data were available on: (1) numerous personal, clinical, occupational, and social variables; (2) type of rehabilitation undertaken; and (3) outcomes following rehabilitation (receiving time loss benefits or undergoing repeat programs). Machine learning, concerned with the design of algorithms to discriminate between classes based on empirical data, was the foundation of our approach to build a classification system with multiple independent and dependent variables. The population included 8,611 unique claimants. Subjects were predominantly employed (85 %) males (64 %) with diagnoses of sprain/strain (44 %). Baseline clinician classification accuracy was high (ROC = 0.86) for selecting programs that lead to successful return-to-work. Classification performance for machine learning techniques outperformed the clinician baseline classification (ROC = 0.94). The final classifiers were multifactorial and included the variables: injury duration, occupation, job attachment status, work status, modified work availability, pain intensity rating, self-rated occupational disability, and 9 items from the SF-36 Health Survey. The use of machine learning classification techniques appears to have resulted in classification performance better than clinician decision-making. The final algorithm has been integrated into a computer-based clinical decision support tool that requires additional validation in a clinical sample.

Scaling Support Vector Machines On Modern HPC Platforms

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

You, Yang; Fu, Haohuan; Song, Shuaiwen

2015-02-01

We designed and implemented MIC-SVM, a highly efficient parallel SVM for x86 based multicore and many-core architectures, such as the Intel Ivy Bridge CPUs and Intel Xeon Phi co-processor (MIC). We propose various novel analysis methods and optimization techniques to fully utilize the multilevel parallelism provided by these architectures and serve as general optimization methods for other machine learning tools.

Differential Laser Doppler based Non-Contact Sensor for Dimensional Inspection with Error Propagation Evaluation

PubMed Central

Mekid, Samir; Vacharanukul, Ketsaya

2006-01-01

To achieve dynamic error compensation in CNC machine tools, a non-contact laser probe capable of dimensional measurement of a workpiece while it is being machined has been developed and presented in this paper. The measurements are automatically fed back to the machine controller for intelligent error compensations. Based on a well resolved laser Doppler technique and real time data acquisition, the probe delivers a very promising dimensional accuracy at few microns over a range of 100 mm. The developed optical measuring apparatus employs a differential laser Doppler arrangement allowing acquisition of information from the workpiece surface. In addition, the measurements are traceable to standards of frequency allowing higher precision.

A study of energy consumption in turning process using lubrication of nanoparticles enhanced coconut oil (NECO)

NASA Astrophysics Data System (ADS)

Mansor, A. F.; Zakaria, M. S.; Azmi, A. I.; Khalil, A. N. M.; Musa, N. A.

2017-10-01

Cutting fluids play very important role in machining application in order to increase tool life, surface finish and reduce energy consumption. Instead of using petrochemical and synthetic based cutting fluids, vegetable oil based lubricants is safety for operators, environmental friendly and become more popular in the industrial applications. This research paper aims to find the advantage of using vegetable oils (coconut oil) with additional of nano particles (CuO) as lubricant to the energy consumption during machining process. The energy was measured for each run from 2 level factorial experimental layout. Obtained results illustrate that lubricant with enhancement of nanoparticles has capability to improve the energy consumption during the machining process.

Design of an ultraprecision computerized numerical control chemical mechanical polishing machine and its implementation

NASA Astrophysics Data System (ADS)

Zhang, Chupeng; Zhao, Huiying; Zhu, Xueliang; Zhao, Shijie; Jiang, Chunye

2018-01-01

The chemical mechanical polishing (CMP) is a key process during the machining route of plane optics. To improve the polishing efficiency and accuracy, a CMP model and machine tool were developed. Based on the Preston equation and the axial run-out error measurement results of the m circles on the tin plate, a CMP model that could simulate the material removal at any point on the workpiece was presented. An analysis of the model indicated that lower axial run-out error led to lower material removal but better polishing efficiency and accuracy. Based on this conclusion, the CMP machine was designed, and the ultraprecision gas hydrostatic guideway and rotary table as well as the Siemens 840Dsl numerical control system were incorporated in the CMP machine. To verify the design principles of machine, a series of detection and machining experiments were conducted. The LK-G5000 laser sensor was employed for detecting the straightness error of the gas hydrostatic guideway and the axial run-out error of the gas hydrostatic rotary table. A 300-mm-diameter optic was chosen for the surface profile machining experiments performed to determine the CMP efficiency and accuracy.

A study on the effect of tool electrode thickness on MRR, and TWR in electrical discharge turning process

NASA Astrophysics Data System (ADS)

Gohil, Vikas; Puri, YM

2018-04-01

Turning by electrical discharge machining (EDM) is an emerging area of research. Generally, wire-EDM is used in EDM turning because it is not concerned with electrode tooling cost. In EDM turning wire electrode leaves cusps on the machined surface because of its small diameters and wire breakage which greatly affect the surface finish of the machined part. Moreover, one of the limitations of the process is low machining speed as compared to constituent processes. In this study, conventional EDM was employed for turning purpose in order to generate free-form cylindrical geometries on difficult-to-cut materials. Therefore, a specially designed turning spindle was mounted on a conventional die-sinking EDM machine to rotate the work piece. A conductive preshaped strip of copper as a forming tool is fed (reciprocate) continuously against the rotating work piece; thus, a mirror image of the tool is formed on the circumference of the work piece. In this way, an axisymmetric work piece can be made with small tools. The developed process is termed as the electrical discharge turning (EDT). In the experiments, the effect of machining parameters, such as pulse-on time, peak current, gap voltage and tool thickness on the MRR, and TWR were investigated and practical machining was carried out by turning of SS-304 stainless steel work piece.

Recent developments in turning hardened steels - A review

NASA Astrophysics Data System (ADS)

Sivaraman, V.; Prakash, S.

2017-05-01

Hard materials ranging from HRC 45 - 68 such as hardened AISI H13, AISI 4340, AISI 52100, D2 STL, D3 STEEL Steel etc., need super hard tool materials to machine. Turning of these hard materials is termed as hard turning. Hard turning makes possible direct machining of the hard materials and also eliminates the lubricant requirement and thus favoring dry machining. Hard turning is a finish turning process and hence conventional grinding is not required. Development of the new advanced super hard tool materials such as ceramic inserts, Cubic Boron Nitride, Polycrystalline Cubic Boron Nitride etc. enabled the turning of these materials. PVD and CVD methods of coating have made easier the production of single and multi layered coated tool inserts. Coatings of TiN, TiAlN, TiC, Al2O3, AlCrN over cemented carbide inserts has lead to the machining of difficult to machine materials. Advancement in the process of hard machining paved way for better surface finish, long tool life, reduced tool wear, cutting force and cutting temperatures. Micro and Nano coated carbide inserts, nanocomposite coated PCBN inserts, micro and nano CBN coated carbide inserts and similar developments have made machining of hardened steels much easier and economical. In this paper, broad literature review on turning of hardened steels including optimizing process parameters, cooling requirements, different tool materials etc., are done.

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.

Prediction of drug synergy in cancer using ensemble-based machine learning techniques

NASA Astrophysics Data System (ADS)

Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder

2018-04-01

Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

A Guide for Industrial Mobilization

DTIC Science & Technology

1989-03-01

packages; and cient, increased production controls may be needed. These actions include: i. Releasing machine tool trigger or- ders and increasing buys...710). the Department of Defense to maintain facili- 4. The National Defense Act authorizes: ties, machine tools , production equipment, and skilled...Defense Industrial Reserve Act pro- Room 3876, U.S. Departm nt of Commerce vides for the reserve of machine tools and other Washington, D.C. 20230 or

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.

A Guide for Planning Facilities for Occupational Preparation Programs in the Machine Trades. Interim Report. Research 24.

ERIC Educational Resources Information Center

Larson, Milton E.

This guide is designed for use by any person or groups of persons responsible for planning occupational programs in the machine trades. Its major purpose is to elicit the necessary information for the writing of educational specifications for facilities to house needed vocational programs in machine tool operation, machine shop, and tool and die…

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.

76 FR 11361 - Defense Federal Acquisition Regulation Supplement; Preservation of Tooling for Major Defense...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-02

... tooling, but should include ``all property, i.e., special test equipment, ground support equipment, machine tools and machines and other intangibles to maintain capability.'' Response: DoD is fully...

Production of rotational parts in small-series and computer-aided planning of its production engineering

NASA Astrophysics Data System (ADS)

Dudas, Illes; Berta, Miklos; Cser, Istvan

1998-12-01

Up-to-date manufacturing equipments of production of rotational parts in small series are lathe-centers and CNC grinding machines with high concentration of manufacturing operations. By the use of these machine tools it can be produced parts with requirements of increased accuracy and surface quality. In the lathe centers, which contain the manufacturing procedures of lathes using stationary tools and of drilling-milling machine tools using rotational tools, non-rotational surfaces of rotational parts can also be produced. The high concentration of manufacturing operations makes necessary the planning and programing of the measuring, monitoring and quality control into the technological process during manufacturing operation. In this way, taking into consideration the technological possibilities of lathe canters, the scope of computer aided technological planning duties significantly increases. It is trivial requirement to give only once the descriptions of the prefabricated parts and ready made parts. Starting taking into account these careful considerations we have been developing the planning system of technology of body of revolution on the base of GTIPROG/EC system which useful for programming of lathe centers. Out paper deals with the results of development and the occurring problems.

Modeling of Geometric Error in Linear Guide Way to Improved the vertical three-axis CNC Milling machine’s accuracy

NASA Astrophysics Data System (ADS)

Kwintarini, Widiyanti; Wibowo, Agung; Arthaya, Bagus M.; Yuwana Martawirya, Yatna

2018-03-01

The purpose of this study was to improve the accuracy of three-axis CNC Milling Vertical engines with a general approach by using mathematical modeling methods of machine tool geometric errors. The inaccuracy of CNC machines can be caused by geometric errors that are an important factor during the manufacturing process and during the assembly phase, and are factors for being able to build machines with high-accuracy. To improve the accuracy of the three-axis vertical milling machine, by knowing geometric errors and identifying the error position parameters in the machine tool by arranging the mathematical modeling. The geometric error in the machine tool consists of twenty-one error parameters consisting of nine linear error parameters, nine angle error parameters and three perpendicular error parameters. The mathematical modeling approach of geometric error with the calculated alignment error and angle error in the supporting components of the machine motion is linear guide way and linear motion. The purpose of using this mathematical modeling approach is the identification of geometric errors that can be helpful as reference during the design, assembly and maintenance stages to improve the accuracy of CNC machines. Mathematically modeling geometric errors in CNC machine tools can illustrate the relationship between alignment error, position and angle on a linear guide way of three-axis vertical milling machines.

Parametric effects of turning Ti-6Al-4V alloys with aluminum oxide nanolubricants with SDBS

NASA Astrophysics Data System (ADS)

Ali, M. A. M.; Azmi, A. I.; Khalil, A. N. M.

2017-09-01

Applications of nanolubricants have been claimed to improve machinability of aerospace metals due to reduction of friction as a results of the rolling action of billions of nanoparticles at the tool-chip interface. In addition, the need to pursue for an eco-friendly machining has pushed researchers toward implementing alternative lubrication methods through minimal quantity lubrication (MQL). However, the gap in the current literature regarding the performance of nanolubricants via MQL has restricted the widespread use of this lubricant and technique in industries. The present work aims to understand the parametric effects of nanoparticles concentration, cutting speed, feed rate and nozzle angle during machining of titanium alloy, Ti-6AL-4V. Multiple performance of machinability outputs such as surface roughness, tool wear and power consumption were simultaneously determined via Taguchi orthogonal array and grey relational analyses. Prior to machining tests, the nanolubricants stabilities were investigated through the addition of surfactant; sodium dodecyl benzene sulfonate (SDBS). The results clearly indicated that inclusion of SDBS surfactant managed to reduce agglomeration in the base lubricant. Meanwhile, grey relational analyses revealed that the combination of 0.6 % nanoparticles concentration, cutting speed of 85 m/min, feed rate of 0.1 mm/rev and nozzle angle of 60o as desired setting for all the three machining outputs.

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

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.

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.

Research on the EDM Technology for Micro-holes at Complex Spatial Locations

NASA Astrophysics Data System (ADS)

Y Liu, J.; Guo, J. M.; Sun, D. J.; Cai, Y. H.; Ding, L. T.; Jiang, H.

2017-12-01

For the demands on machining micro-holes at complex spatial location, several key technical problems are conquered such as micro-Electron Discharge Machining (micro-EDM) power supply system’s development, the host structure’s design and machining process technical. Through developing low-voltage power supply circuit, high-voltage circuit, micro and precision machining circuit and clearance detection system, the narrow pulse and high frequency six-axis EDM machining power supply system is developed to meet the demands on micro-hole discharging machining. With the method of combining the CAD structure design, CAE simulation analysis, modal test, ODS (Operational Deflection Shapes) test and theoretical analysis, the host construction and key axes of the machine tool are optimized to meet the position demands of the micro-holes. Through developing the special deionized water filtration system to make sure that the machining process is stable enough. To verify the machining equipment and processing technical developed in this paper through developing the micro-hole’s processing flow and test on the real machine tool. As shown in the final test results: the efficient micro-EDM machining pulse power supply system, machine tool host system, deionized filtration system and processing method developed in this paper meet the demands on machining micro-holes at complex spatial locations.

Microcomputer-Based Access to Machine-Readable Numeric Databases.

ERIC Educational Resources Information Center

Wenzel, Patrick

1988-01-01

Describes the use of microcomputers and relational database management systems to improve access to numeric databases by the Data and Program Library Service at the University of Wisconsin. The internal records management system, in-house reference tools, and plans to extend these tools to the entire campus are discussed. (3 references) (CLB)

78 FR 28111 - Making Open and Machine Readable the New Default for Government Information

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-14

... warning systems, location-based applications, precision farming tools, and much more, improving Americans... repository of tools and best practices to assist agencies in integrating the Open Data Policy into their... needed to ensure it remains a resource to facilitate the adoption of open data practices. (b) Within 90...

Role of artificial intelligence in the care of patients with nonsmall cell lung cancer.

PubMed

Rabbani, Mohamad; Kanevsky, Jonathan; Kafi, Kamran; Chandelier, Florent; Giles, Francis J

2018-04-01

Lung cancer is the leading cause of cancer death worldwide. In up to 57% of patients, it is diagnosed at an advanced stage and the 5-year survival rate ranges between 10%-16%. There has been a significant amount of research using machine learning to generate tools using patient data to improve outcomes. This narrative review is based on research material obtained from PubMed up to Nov 2017. The search terms include "artificial intelligence," "machine learning," "lung cancer," "Nonsmall Cell Lung Cancer (NSCLC)," "diagnosis" and "treatment." Recent studies support the use of computer-aided systems and the use of radiomic features to help diagnose lung cancer earlier. Other studies have looked at machine learning (ML) methods that offer prognostic tools to doctors and help them in choosing personalized treatment options for their patients based on molecular, genetics and histological features. Combining artificial intelligence approaches into health care may serve as a beneficial tool for patients with NSCLC, and this review outlines these benefits and current shortcomings throughout the continuum of care. We present a review of the various applications of ML methods in NSCLC as it relates to improving diagnosis, treatment and outcomes. © 2018 Stichting European Society for Clinical Investigation Journal Foundation.

Toolpath Strategy and Optimum Combination of Machining Parameter during Pocket Mill Process of Plastic Mold Steels Material

NASA Astrophysics Data System (ADS)

Wibowo, Y. T.; Baskoro, S. Y.; Manurung, V. A. T.

2018-02-01

Plastic based products spread all over the world in many aspects of life. The ability to substitute other materials is getting stronger and wider. The use of plastic materials increases and become unavoidable. Plastic based mass production requires injection process as well Mold. The milling process of plastic mold steel material was done using HSS End Mill cutting tool that is widely used in a small and medium enterprise for the reason of its ability to be re sharpened and relatively inexpensive. Study on the effect of the geometry tool states that it has an important effect on the quality improvement. Cutting speed, feed rate, depth of cut and radii are input parameters beside to the tool path strategy. This paper aims to investigate input parameter and cutting tools behaviors within some different tool path strategy. For the reason of experiments efficiency Taguchi method and ANOVA were used. Response studied is surface roughness and cutting behaviors. By achieving the expected quality, no more additional process is required. Finally, the optimal combination of machining parameters will deliver the expected roughness and of course totally reduced cutting time. However actually, SMEs do not optimally use this data for cost reduction.

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

Temperature Measurement and Numerical Prediction in Machining Inconel 718.

PubMed

Díaz-Álvarez, José; Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-06-30

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning.

Artificial Neural Networks as an Architectural Design Tool-Generating New Detail Forms Based On the Roman Corinthian Order Capital

NASA Astrophysics Data System (ADS)

Radziszewski, Kacper

2017-10-01

The following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital. During the experiment, as an input training data set, five local geometry parameters combined has given the best results: Theta, Pi, Rho in spherical coordinate system based on the capital volume centroid, followed by Z value of the Cartesian coordinate system and a distance from vertical planes created based on the capital symmetry. Additionally during the experiment, artificial neural network hidden layers optimal count and structure was found, giving results of the error below 0.2% for the mentioned before input parameters. Once successfully trained artificial network, was able to mimic the details composition on any other geometry type given. Despite of calculating the transformed geometry locally and separately for each of the thousands of surface points, system could create visually attractive and diverse, complex patterns. Designed tool, based on the supervised learning method of machine learning, gives possibility of generating new architectural forms- free of the designer’s imagination bounds. Implementing the infinitely broad computational methods of machine learning, or Artificial Intelligence in general, not only could accelerate and simplify the design process, but give an opportunity to explore never seen before, unpredictable forms or everyday architectural practice solutions.

Aggregation of Electric Current Consumption Features to Extract Maintenance KPIs

NASA Astrophysics Data System (ADS)

Simon, Victor; Johansson, Carl-Anders; Galar, Diego

2017-09-01

All electric powered machines offer the possibility of extracting information and calculating Key Performance Indicators (KPIs) from the electric current signal. Depending on the time window, sampling frequency and type of analysis, different indicators from the micro to macro level can be calculated for such aspects as maintenance, production, energy consumption etc. On the micro-level, the indicators are generally used for condition monitoring and diagnostics and are normally based on a short time window and a high sampling frequency. The macro indicators are normally based on a longer time window with a slower sampling frequency and are used as indicators for overall performance, cost or consumption. The indicators can be calculated directly from the current signal but can also be based on a combination of information from the current signal and operational data like rpm, position etc. One or several of those indicators can be used for prediction and prognostics of a machine's future behavior. This paper uses this technique to calculate indicators for maintenance and energy optimization in electric powered machines and fleets of machines, especially machine tools.

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features

PubMed Central

Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-01-01

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization. PMID:28599282

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

PubMed

Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-07-18

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

JPRS Report, Science & Technology, Europe & Latin America.

DTIC Science & Technology

1988-01-22

Rex Malik; ZERO UN INFORMATIQUE, 31 Aug 87) 25 FACTORY AUTOMATION, ROBOTICS West Europe Seeks To Halt Japanese Inroads in Machine Tool Sector...aircraft. 25048 CSO: 3698/A014 26 FACTORY AUTOMATION, ROBOTICS vrEST EUROpE WEST EUROPE SEEKS TO HALT JAPANESE INROADS IN MACHINE TOOL SECTOR...Trumpf, by the same journalist; first paragraph is L’USINE NOUVELLE introduction] [Excerpts] European machine - tool builders are stepping up mutual

Translations on North Korea No. 622

DTIC Science & Technology

1978-10-13

Pyongyang Power Station 5 July Electric Factory Hamhung Machine Tool Factory Kosan Plastic Pipe Factory Sog’wangea Plastic Pipe Factory 8...August Factory Double Chollima Hamhung Disabled Veterans’ Plastic Goods Factory Mangyongdae Machine Tool Factory Kangso Coal Mine Tongdaewon Garment...21 Jul 78 p 4) innovating in machine tool production (NC 21 Jul 78 p 2) in 40 days of the 蔴 days of combat" raised coal production 10 percent

Pellet to Part Manufacturing System for CNCs

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

Roschli, Alex C.; Love, Lonnie J.; Post, Brian K.

Oak Ridge National Laboratory’s Manufacturing Demonstration Facility worked with Hybrid Manufacturing Technologies to develop a compact prototype composite additive manufacturing head that can effectively extrude injection molding pellets. The head interfaces with conventional CNC machine tools enabling rapid conversion of conventional machine tools to additive manufacturing tools. The intent was to enable wider adoption of Big Area Additive Manufacturing (BAAM) technology and combine BAAM technology with conventional machining systems.

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…

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.

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

Wire EDM for Refractory Materials

NASA Technical Reports Server (NTRS)

Zellars, G. R.; Harris, F. E.; Lowell, C. E.; Pollman, W. M.; Rys, V. J.; Wills, R. J.

1982-01-01

In an attempt to reduce fabrication time and costs, Wire Electrical Discharge Machine (Wire EDM) method was investigated as tool for fabricating matched blade roots and disk slots. Eight high-strength nickel-base superalloys were used. Computer-controlled Wire EDM technique provided high quality surfaces with excellent dimensional tolerances. Wire EDM method offers potential for substantial reductions in fabrication costs for "hard to machine" alloys and electrically conductive materials in specific high-precision applications.

Classification and authentication of unknown water samples using machine learning algorithms.

PubMed

Kundu, Palash K; Panchariya, P C; Kundu, Madhusree

2011-07-01

This paper proposes the development of water sample classification and authentication, in real life which is based on machine learning algorithms. The proposed techniques used experimental measurements from a pulse voltametry method which is based on an electronic tongue (E-tongue) instrumentation system with silver and platinum electrodes. E-tongue include arrays of solid state ion sensors, transducers even of different types, data collectors and data analysis tools, all oriented to the classification of liquid samples and authentication of unknown liquid samples. The time series signal and the corresponding raw data represent the measurement from a multi-sensor system. The E-tongue system, implemented in a laboratory environment for 6 numbers of different ISI (Bureau of Indian standard) certified water samples (Aquafina, Bisleri, Kingfisher, Oasis, Dolphin, and McDowell) was the data source for developing two types of machine learning algorithms like classification and regression. A water data set consisting of 6 numbers of sample classes containing 4402 numbers of features were considered. A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system. A proposed partial least squares (PLS) based classifier, which was dedicated as well; to authenticate a specific category of water sample evolved out as an integral part of the E-tongue instrumentation system. The developed PCA and PLS based E-tongue system emancipated an overall encouraging authentication percentage accuracy with their excellent performances for the aforesaid categories of water samples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Prospect of EUV mask repair technology using e-beam tool

NASA Astrophysics Data System (ADS)

Kanamitsu, Shingo; Hirano, Takashi; Suga, Osamu

2010-09-01

Currently, repair machines used for advanced photomasks utilize principle method like as FIB, AFM, and EB. There are specific characteristic respectively, thus they have an opportunity to be used in suitable situation. But when it comes to EUV generation, pattern size is so small highly expected as under 80nm that higher image resolution and repair accuracy is needed for its machines. Because FIB machine has intrinsic damage problem induced by Ga ion and AFM machine has critical tip size issue, those machines are basically difficult to be applied for EUV generation. Consequently, we focused on EB repair tool for research work. EB repair tool has undergone practical milestone about MoSi based masks. We have applied same process which is used for MoSi to EUV blank and confirmed its reaction. Then we found some severe problems which show uncontrollable feature due to its enormously strong reaction between etching gas and absorber material. Though we could etch opaque defect with conventional method and get the edge shaped straight by top-down SEM viewing, there were problems like as sidewall undercut or local erosion depending on defect shape. In order to cope with these problems, the tool vender has developed a new process and reported it through an international conference [1]. We have evaluated the new process mentioned above in detail. In this paper, we will bring the results of those evaluations. Several experiments for repair accuracy, process stability, and other items have been done under estimation of practical condition assuming diversified size and shape defects. A series of actual printability tests will be also included. On the basis of these experiments, we consider the possibility of EB-repair application for 20nm pattern.

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.

Hardware assisted hypervisor introspection.

PubMed

Shi, Jiangyong; Yang, Yuexiang; Tang, Chuan

2016-01-01

In this paper, we introduce hypervisor introspection, an out-of-box way to monitor the execution of hypervisors. Similar to virtual machine introspection which has been proposed to protect virtual machines in an out-of-box way over the past decade, hypervisor introspection can be used to protect hypervisors which are the basis of cloud security. Virtual machine introspection tools are usually deployed either in hypervisor or in privileged virtual machines, which might also be compromised. By utilizing hardware support including nested virtualization, EPT protection and #BP, we are able to monitor all hypercalls belongs to the virtual machines of one hypervisor, include that of privileged virtual machine and even when the hypervisor is compromised. What's more, hypercall injection method is used to simulate hypercall-based attacks and evaluate the performance of our method. Experiment results show that our method can effectively detect hypercall-based attacks with some performance cost. Lastly, we discuss our furture approaches of reducing the performance cost and preventing the compromised hypervisor from detecting the existence of our introspector, in addition with some new scenarios to apply our hypervisor introspection system.

Large robotized turning centers described

NASA Astrophysics Data System (ADS)

Kirsanov, V. V.; Tsarenko, V. I.

1985-09-01

The introduction of numerical control (NC) machine tools has made it possible to automate machining in series and small series production. The organization of automated production sections merged NC machine tools with automated transport systems. However, both the one and the other require the presence of an operative at the machine for low skilled operations. Industrial robots perform a number of auxiliary operations, such as equipment loading-unloading and control, changing cutting and auxiliary tools, controlling workpieces and parts, and cleaning of location surfaces. When used with a group of equipment they perform transfer operations between the machine tools. Industrial robots eliminate the need for workers to form auxiliary operations. This underscores the importance of developing robotized manufacturing centers providing for minimal human participation in production and creating conditions for two and three shift operation of equipment. Work carried out at several robotized manufacturing centers for series and small series production is described.

An experimental study of flank wear in the end milling of AISI 316 stainless steel with coated carbide inserts

NASA Astrophysics Data System (ADS)

Odedeyi, P. B.; Abou-El-Hossein, K.; Liman, M.

2017-05-01

Stainless steel 316 is a difficult-to-machine iron-based alloys that contain minimum of about 12% of chromium commonly used in marine and aerospace industry. This paper presents an experimental study of the tool wear propagation variations in the end milling of stainless steel 316 with coated carbide inserts. The milling tests were conducted at three different cutting speeds while feed rate and depth of cut were at (0.02, 0.06 and 01) mm/rev and (1, 2 and 3) mm, respectively. The cutting tool used was TiAlN-PVD-multi-layered coated carbides. The effects of cutting speed, cutting tool coating top layer and workpiece material were investigated on the tool life. The results showed that cutting speed significantly affected the machined flank wears values. With increasing cutting speed, the flank wear values decreased. The experimental results showed that significant flank wear was the major and predominant failure mode affecting the tool life.

Kernel based machine learning algorithm for the efficient prediction of type III polyketide synthase family of proteins.

PubMed

Mallika, V; Sivakumar, K C; Jaichand, S; Soniya, E V

2010-07-13

Type III Polyketide synthases (PKS) are family of proteins considered to have significant roles in the biosynthesis of various polyketides in plants, fungi and bacteria. As these proteins shows positive effects to human health, more researches are going on regarding this particular protein. Developing a tool to identify the probability of sequence being a type III polyketide synthase will minimize the time consumption and manpower efforts. In this approach, we have designed and implemented PKSIIIpred, a high performance prediction server for type III PKS where the classifier is Support Vector Machines (SVMs). Based on the limited training dataset, the tool efficiently predicts the type III PKS superfamily of proteins with high sensitivity and specificity. The PKSIIIpred is available at http://type3pks.in/prediction/. We expect that this tool may serve as a useful resource for type III PKS researchers. Currently work is being progressed for further betterment of prediction accuracy by including more sequence features in the training dataset.

Nutrition environment measures survey-vending: development, dissemination, and reliability.

PubMed

Voss, Carol; Klein, Susan; Glanz, Karen; Clawson, Margaret

2012-07-01

Researchers determined a need to develop an instrument to assess the vending machine environment that was comparably reliable and valid to other Nutrition Environment Measures Survey tools and that would provide consistent and comparable data for businesses, schools, and communities. Tool development, reliability testing, and dissemination of the Nutrition Environment Measures Survey-Vending (NEMS-V) involved a collaboration of students, professionals, and community leaders. Interrater reliability testing showed high levels of agreement among trained raters on the products and evaluations of products. NEMS-V can benefit public health partners implementing policy and environmental change initiatives as a part of their community wellness activities. The vending machine project will support a policy calling for state facilities to provide a minimum of 30% of foods and beverages in vending machines as healthy options, based on NEMS-V criteria, which will be used as a model for other businesses.

A new methodology for predictive tool wear

NASA Astrophysics Data System (ADS)

Kim, Won-Sik

An empirical approach to tool wear, which requires a series of machining tests for each combination of insert and work material, has been a standard practice for industries since early part of the twentieth century. With many varieties of inserts and work materials available for machining, the empirical approach is too experiment-intensive that the demand for the development of a model-based approach is increasing. With a model-based approach, the developed wear equation can be extended without additional machining experiments. The main idea is that the temperatures on the primary wear areas are increasing such that the physical properties of the tool material degrade substantially and consequently tool wear increases. Dissolution and abrasion are identified to be the main mechanisms for tool wear. Flank wear is predominantly a phenomenon of abrasion as evident by the presence of a scoring mark on the flank surface. Based on this statement, it is reasonable to expect that the flank-wear rate would increase with the content of hard inclusions. However, experimental flank wear results did not necessary correspond to the content of cementite phase present in the steels. Hence, other phenomena are believed to significantly affect wear behavior under certain conditions. When the cutting temperature in the flank interface is subjected to high enough temperatures, pearlitic structure austenizes. During the formation of a new austenitic phase, the existing carbon is dissolved into the ferrite matrix, which will reduce the abrasive action. To verify the austenitic transformation, turning tests were conducted with plain carbon steels. The machined surface areas are imaged using X-ray diffraction the Scanning Electron Microscope (SEM) and the Transmission Electron Microscope (TEM). On the other hand, crater wear occurs as a result of dissolution wear and abrasive wear. To verify the wear mechanisms of crater wear, various coating inserts as well as uncoated inserts were turned with various cutting conditions and the results were compared with the proposed analytical wear models. The crater surfaces after machining have been carefully studied to shed light on the physics behind the crater wear. In addition, the abrasive wear mechanism plays a major role in the development of crater wear. Laser shock processing (LSP) has been applied to locally relieve the deleterious tensile residual stresses on the crater surface of a coated tool, thus to improve the hardness of the coating. This thesis shows that LSP has indeed improve wear resistance of CVD coated alumina tool inserts, which has residual stress due to high processing temperature. LSP utilizes a very short laser pulse with high energy density, which induces high-pressure stress wave propagation. The residual stresses are relieved by incident shock waves on the coating surface. Residual stress levels of LSP CVD alumina-coated carbide insert were evaluated by the X-ray diffractometer. Based on these results, LSP parameters such as number of laser pulses and laser energy density can be controlled to reduce residual stress. Crater wear shows that the wear resistance increase with LSP treated tool inserts. Because the hardness data are used to predict the wear, the improvement in hardness and wear resistance shows that the mechanism of crater wear also involves abrasive wear.

Optimization of machining parameters in dry EDM of EN31 steel

NASA Astrophysics Data System (ADS)

Brar, G. S.

2018-03-01

Dry electric discharge machining (Dry EDM) is one of the novel EDM technology in which gases namely helium, argon, oxygen, nitrogen etc. are used as a dielectric medium at high pressure instead of oil based liquid dielectric. The present study investigates dry electric discharge machining (with rotary tool) of EN-31 steel to achieve lower tool wear rate (TWR) and better surface roughness (Ra) by performing a set of exploratory experiments with oxygen gas as dielectric. The effect of polarity, discharge current, gas flow pressure, pulse-on time, R.P.M. and gap voltage on the MRR, TWR and surface roughness (Ra) in dry EDM was studied with copper as rotary tool. The significant factors affecting MRR are discharge current and pulse on time. The significant factors affecting TWR are gas flow pressure, pulse on time and R.P.M. TWR was found close to zero in most of the experiments. The significant factors affecting Ra are pulse on time, gas flow pressure and R.P.M. It was found that polarity has nearly zero effect on all the three output variables.

Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

PubMed

Badal-Valero, Elena; Alvarez-Jareño, José A; Pavía, Jose M

2018-01-01

This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. We combine Benford's Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the context of a real Spanish court case. After mapping each supplier's set of accounting data into a 21-dimensional space using Benford's Law and applying machine learning algorithms, additional companies that could merit further scrutiny are flagged up. A new tool to detect money laundering criminals is proposed in this paper. The tool is tested in the context of a real case. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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…

29 CFR 1926.303 - Abrasive wheels and tools.

Code of Federal Regulations, 2013 CFR

2013-07-01

... and tools. (a) Power. All grinding machines shall be supplied with sufficient power to maintain the spindle speed at safe levels under all conditions of normal operation. (b) Guarding. (1) Grinding machines..., nut, and outer flange may be exposed on machines designed as portable saws. (c) Use of abrasive wheels...

29 CFR 1926.303 - Abrasive wheels and tools.

Code of Federal Regulations, 2014 CFR

2014-07-01

... and tools. (a) Power. All grinding machines shall be supplied with sufficient power to maintain the spindle speed at safe levels under all conditions of normal operation. (b) Guarding. (1) Grinding machines..., nut, and outer flange may be exposed on machines designed as portable saws. (c) Use of abrasive wheels...

29 CFR 1926.303 - Abrasive wheels and tools.

Code of Federal Regulations, 2012 CFR

2012-07-01

... and tools. (a) Power. All grinding machines shall be supplied with sufficient power to maintain the spindle speed at safe levels under all conditions of normal operation. (b) Guarding. (1) Grinding machines..., nut, and outer flange may be exposed on machines designed as portable saws. (c) Use of abrasive wheels...

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.

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.

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

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.

Vibrations Detection in Industrial Pumps Based on Spectral Analysis to Increase Their Efficiency

NASA Astrophysics Data System (ADS)

Rachid, Belhadef; Hafaifa, Ahmed; Boumehraz, Mohamed

2016-03-01

Spectral analysis is the key tool for the study of vibration signals in rotating machinery. In this work, the vibration analysis applied for conditional preventive maintenance of such machines is proposed, as part of resolved problems related to vibration detection on the organs of these machines. The vibration signal of a centrifugal pump was treated to mount the benefits of the approach proposed. The obtained results present the signal estimation of a pump vibration using Fourier transform technique compared by the spectral analysis methods based on Prony approach.

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.

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.

Automated condition-invariable neurite segmentation and synapse classification using textural analysis-based machine-learning algorithms

PubMed Central

Kandaswamy, Umasankar; Rotman, Ziv; Watt, Dana; Schillebeeckx, Ian; Cavalli, Valeria; Klyachko, Vitaly

2013-01-01

High-resolution live-cell imaging studies of neuronal structure and function are characterized by large variability in image acquisition conditions due to background and sample variations as well as low signal-to-noise ratio. The lack of automated image analysis tools that can be generalized for varying image acquisition conditions represents one of the main challenges in the field of biomedical image analysis. Specifically, segmentation of the axonal/dendritic arborizations in brightfield or fluorescence imaging studies is extremely labor-intensive and still performed mostly manually. Here we describe a fully automated machine-learning approach based on textural analysis algorithms for segmenting neuronal arborizations in high-resolution brightfield images of live cultured neurons. We compare performance of our algorithm to manual segmentation and show that it combines 90% accuracy, with similarly high levels of specificity and sensitivity. Moreover, the algorithm maintains high performance levels under a wide range of image acquisition conditions indicating that it is largely condition-invariable. We further describe an application of this algorithm to fully automated synapse localization and classification in fluorescence imaging studies based on synaptic activity. Textural analysis-based machine-learning approach thus offers a high performance condition-invariable tool for automated neurite segmentation. PMID:23261652

Improving Energy Efficiency in CNC Machining

NASA Astrophysics Data System (ADS)

Pavanaskar, Sushrut S.

We present our work on analyzing and improving the energy efficiency of multi-axis CNC milling process. Due to the differences in energy consumption behavior, we treat 3- and 5-axis CNC machines separately in our work. For 3-axis CNC machines, we first propose an energy model that estimates the energy requirement for machining a component on a specified 3-axis CNC milling machine. Our model makes machine-specific predictions of energy requirements while also considering the geometric aspects of the machining toolpath. Our model - and the associated software tool - facilitate direct comparison of various alternative toolpath strategies based on their energy-consumption performance. Further, we identify key factors in toolpath planning that affect energy consumption in CNC machining. We then use this knowledge to propose and demonstrate a novel toolpath planning strategy that may be used to generate new toolpaths that are inherently energy-efficient, inspired by research on digital micrography -- a form of computational art. For 5-axis CNC machines, the process planning problem consists of several sub-problems that researchers have traditionally solved separately to obtain an approximate solution. After illustrating the need to solve all sub-problems simultaneously for a truly optimal solution, we propose a unified formulation based on configuration space theory. We apply our formulation to solve a problem variant that retains key characteristics of the full problem but has lower dimensionality, allowing visualization in 2D. Given the complexity of the full 5-axis toolpath planning problem, our unified formulation represents an important step towards obtaining a truly optimal solution. With this work on the two types of CNC machines, we demonstrate that without changing the current infrastructure or business practices, machine-specific, geometry-based, customized toolpath planning can save energy in CNC machining.

Experimental Study of Tool Wear and Grinding Forces During BK-7 Glass Micro-grinding with Modified PCD Tool

NASA Astrophysics Data System (ADS)

Pratap, A.; Sahoo, P.; Patra, K.; Dyakonov, A. A.

2017-09-01

This study focuses on the improvement in grinding performance of BK-7 glass using polycrystalline diamond micro-tool. Micro-tools are modified using wire EDM and performance of modified tools is compared with that of as received tool. Tool wear of different types of tools are observed. To quantify the tool wear, a method based on weight loss of tool is introduced in this study. Modified tools significantly reduce tool wear in comparison to the normal tool. Grinding forces increase with machining time due to tool wear. However, modified tools produce lesser forces thus can improve life of the PCD micro-grinding tool.

Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.

PubMed

Citak-Er, Fusun; Firat, Zeynep; Kovanlikaya, Ilhami; Ture, Ugur; Ozturk-Isik, Esin

2018-06-15

The objective of this study was to assess the contribution of multi-parametric (mp) magnetic resonance imaging (MRI) quantitative features in the machine learning-based grading of gliomas with a multi-region-of-interests approach. Forty-three patients who were newly diagnosed as having a glioma were included in this study. The patients were scanned prior to any therapy using a standard brain tumor magnetic resonance (MR) imaging protocol that included T1 and T2-weighted, diffusion-weighted, diffusion tensor, MR perfusion and MR spectroscopic imaging. Three different regions-of-interest were drawn for each subject to encompass tumor, immediate tumor periphery, and distant peritumoral edema/normal. The normalized mp-MRI features were used to build machine-learning models for differentiating low-grade gliomas (WHO grades I and II) from high grades (WHO grades III and IV). In order to assess the contribution of regional mp-MRI quantitative features to the classification models, a support vector machine-based recursive feature elimination method was applied prior to classification. A machine-learning model based on support vector machine algorithm with linear kernel achieved an accuracy of 93.0%, a specificity of 86.7%, and a sensitivity of 96.4% for the grading of gliomas using ten-fold cross validation based on the proposed subset of the mp-MRI features. In this study, machine-learning based on multiregional and multi-parametric MRI data has proven to be an important tool in grading glial tumors accurately even in this limited patient population. Future studies are needed to investigate the use of machine learning algorithms for brain tumor classification in a larger patient cohort. Copyright © 2018. Published by Elsevier Ltd.

Post hoc support vector machine learning for impedimetric biosensors based on weak protein-ligand interactions.

PubMed

Rong, Y; Padron, A V; Hagerty, K J; Nelson, N; Chi, S; Keyhani, N O; Katz, J; Datta, S P A; Gomes, C; McLamore, E S

2018-04-30

Impedimetric biosensors for measuring small molecules based on weak/transient interactions between bioreceptors and target analytes are a challenge for detection electronics, particularly in field studies or in the analysis of complex matrices. Protein-ligand binding sensors have enormous potential for biosensing, but achieving accuracy in complex solutions is a major challenge. There is a need for simple post hoc analytical tools that are not computationally expensive, yet provide near real time feedback on data derived from impedance spectra. Here, we show the use of a simple, open source support vector machine learning algorithm for analyzing impedimetric data in lieu of using equivalent circuit analysis. We demonstrate two different protein-based biosensors to show that the tool can be used for various applications. We conclude with a mobile phone-based demonstration focused on the measurement of acetone, an important biomarker related to the onset of diabetic ketoacidosis. In all conditions tested, the open source classifier was capable of performing as well as, or better, than the equivalent circuit analysis for characterizing weak/transient interactions between a model ligand (acetone) and a small chemosensory protein derived from the tsetse fly. In addition, the tool has a low computational requirement, facilitating use for mobile acquisition systems such as mobile phones. The protocol is deployed through Jupyter notebook (an open source computing environment available for mobile phone, tablet or computer use) and the code was written in Python. For each of the applications, we provide step-by-step instructions in English, Spanish, Mandarin and Portuguese to facilitate widespread use. All codes were based on scikit-learn, an open source software machine learning library in the Python language, and were processed in Jupyter notebook, an open-source web application for Python. The tool can easily be integrated with the mobile biosensor equipment for rapid detection, facilitating use by a broad range of impedimetric biosensor users. This post hoc analysis tool can serve as a launchpad for the convergence of nanobiosensors in planetary health monitoring applications based on mobile phone hardware.

Experimental investigation into effect of cutting parameters on surface integrity of hardened tool steel

NASA Astrophysics Data System (ADS)

Bashir, K.; Alkali, A. U.; Elmunafi, M. H. S.; Yusof, N. M.

2018-04-01

Recent trend in turning hardened materials have gained popularity because of its immense machinability benefits. However, several machining processes like thermal assisted machining and cryogenic machining have reveal superior machinability benefits over conventional dry turning of hardened materials. Various engineering materials have been studied. However, investigations on AISI O1 tool steel have not been widely reported. In this paper, surface finish and surface integrity dominant when hard turning AISI O1 tool steel is analysed. The study is focused on the performance of wiper coated ceramic tool with respect to surface roughness and surface integrity of hardened tool steel. Hard turned tool steel was machined at varying cutting speed of 100, 155 and 210 m/min and feed rate of 0.05, 0.125 and 0.20mm/rev. The depth of cut of 0.2mm was maintained constant throughout the machining trials. Machining was conducted using dry turning on 200E-axis CNC lathe. The experimental study revealed that the surface finish is relatively superior at higher cutting speed of 210m/min. The surface finish increases when cutting speed increases whereas surface finish is generally better at lower feed rate of 0.05mm/rev. The experimental study conducted have revealed that phenomena such as work piece vibration due to poor or improper mounting on the spindle also contributed to higher surface roughness value of 0.66Ra during turning at 0.2mm/rev. Traces of white layer was observed when viewed with optical microscope which shows evidence of cutting effects on the turned work material at feed rate of 0.2 rev/min

Machine Learning-Based App for Self-Evaluation of Teacher-Specific Instructional Style and Tools

ERIC Educational Resources Information Center

Duzhin, Fedor; Gustafsson, Anders

2018-01-01

Course instructors need to assess the efficacy of their teaching methods, but experiments in education are seldom politically, administratively, or ethically feasible. Quasi-experimental tools, on the other hand, are often problematic, as they are typically too complicated to be of widespread use to educators and may suffer from selection bias…

Supporting Open Access to European Academic Courses: The ASK-CDM-ECTS Tool

ERIC Educational Resources Information Center

Sampson, Demetrios G.; Zervas, Panagiotis

2013-01-01

Purpose: This paper aims to present and evaluate a web-based tool, namely ASK-CDM-ECTS, which facilitates authoring and publishing on the web descriptions of (open) academic courses in machine-readable format using an application profile of the Course Description Metadata (CDM) specification, namely CDM-ECTS. Design/methodology/approach: The paper…

Mind Maps: Hot New Tools Proposed for Cyberspace Librarians.

ERIC Educational Resources Information Center

Humphreys, Nancy K.

1999-01-01

Describes how online searchers can use a software tool based on back-of-the-book indexes to assist in dealing with search engine databases compiled by spiders that crawl across the entire Internet or through large Web sites. Discusses human versus machine knowledge, conversion of indexes to mind maps or mini-thesauri, middleware, eXtensible Markup…

Machinability assessment of commercially pure titanium (CP-Ti) during turning operation: Application potential of GRA method

NASA Astrophysics Data System (ADS)

Khan, Akhtar; Maity, Kalipada

2018-03-01

This paper explores some of the vital machinability characteristics of commercially pure titanium (CP-Ti) grade 2. Experiments were conducted based on Taguchi’s L9 orthogonal array. The selected material was machined on a heavy duty lathe (Model: HMT NH26) using uncoated carbide inserts in dry cutting environment. The selected inserts were designated by ISO as SNMG 120408 (Model: K313) and manufactured by Kennametal. These inserts were rigidly mounted on a right handed tool holder PSBNR 2020K12. Cutting speed, feed rate and depth of cut were selected as three input variables whereas tool wear (VBc) and surface roughness (Ra) were the major attentions. In order to confirm an appreciable machinability of the work part, an optimal parametric combination was attained with the help of grey relational analysis (GRA) approach. Finally, a mathematical model was developed to exhibit the accuracy and acceptability of the proposed methodology using multiple regression equations. The results indicated that, the suggested model is capable of predicting overall grey relational grade within acceptable range.

Strategies for single-point diamond machining a large format germanium blazed immersion grating

NASA Astrophysics Data System (ADS)

Montesanti, R. C.; Little, S. L.; Kuzmenko, P. J.; Bixler, J. V.; Jackson, J. L.; Lown, J. G.; Priest, R. E.; Yoxall, B. E.

2016-07-01

A large format germanium immersion grating was flycut with a single-point diamond tool on the Precision Engineering Research Lathe (PERL) at the Lawrence Livermore National Laboratory (LLNL) in November - December 2015. The grating, referred to as 002u, has an area of 59 mm x 67 mm (along-groove and cross-groove directions), line pitch of 88 line/mm, and blaze angle of 32 degree. Based on total groove length, the 002u grating is five times larger than the previous largest grating (ZnSe) cut on PERL, and forty-five times larger than the previous largest germanium grating cut on PERL. The key risks associated with cutting the 002u grating were tool wear and keeping the PERL machine running uninterrupted in a stable machining environment. This paper presents the strategies employed to mitigate these risks, introduces pre-machining of the as-etched grating substrate to produce a smooth, flat, damage-free surface into which the grooves are cut, and reports on trade-offs that drove decisions and experimental results.

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.

A Collaborative Framework for Distributed Privacy-Preserving Support Vector Machine Learning

PubMed Central

Que, Jialan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

A Support Vector Machine (SVM) is a popular tool for decision support. The traditional way to build an SVM model is to estimate parameters based on a centralized repository of data. However, in the field of biomedicine, patient data are sometimes stored in local repositories or institutions where they were collected, and may not be easily shared due to privacy concerns. This creates a substantial barrier for researchers to effectively learn from the distributed data using machine learning tools like SVMs. To overcome this difficulty and promote efficient information exchange without sharing sensitive raw data, we developed a Distributed Privacy Preserving Support Vector Machine (DPP-SVM). The DPP-SVM enables privacy-preserving collaborative learning, in which a trusted server integrates “privacy-insensitive” intermediary results. The globally learned model is guaranteed to be exactly the same as learned from combined data. We also provide a free web-service (http://privacy.ucsd.edu:8080/ppsvm/) for multiple participants to collaborate and complete the SVM-learning task in an efficient and privacy-preserving manner. PMID:23304414

Mycofier: a new machine learning-based classifier for fungal ITS sequences.

PubMed

Delgado-Serrano, Luisa; Restrepo, Silvia; Bustos, Jose Ricardo; Zambrano, Maria Mercedes; Anzola, Juan Manuel

2016-08-11

The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level. A fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level. The final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git .

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.

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.

Support vector machines-based fault diagnosis for turbo-pump rotor

NASA Astrophysics Data System (ADS)

Yuan, Sheng-Fa; Chu, Fu-Lei

2006-05-01

Most artificial intelligence methods used in fault diagnosis are based on empirical risk minimisation principle and have poor generalisation when fault samples are few. Support vector machines (SVM) is a new general machine-learning tool based on structural risk minimisation principle that exhibits good generalisation even when fault samples are few. Fault diagnosis based on SVM is discussed. Since basic SVM is originally designed for two-class classification, while most of fault diagnosis problems are multi-class cases, a new multi-class classification of SVM named 'one to others' algorithm is presented to solve the multi-class recognition problems. It is a binary tree classifier composed of several two-class classifiers organised by fault priority, which is simple, and has little repeated training amount, and the rate of training and recognition is expedited. The effectiveness of the method is verified by the application to the fault diagnosis for turbo pump rotor.

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision

PubMed Central

Wu, Dung-Sheng

2018-01-01

Spark-assisted chemical engraving (SACE) is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool electrode was pre-pressured on the quartz glass surface to feed the electrode that was in contact with the machining surface of the quartz glass. In situ image acquisition and analysis of the SACE drilling processes were used to analyze the captured image of the state of the spark discharge at the tip and sidewall of the electrode. The results indicated an association between the accumulative size of the SACE-induced spark area and deepness of the hole. The results indicated that the evaluated depths of the SACE-machined holes were a proportional function of the accumulative spark size with a high degree of correlation. The study proposes an innovative computer vision-based method to estimate the deepness and status of SACE-drilled holes in real time. PMID:29565303

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision.

PubMed

Ho, Chao-Ching; Wu, Dung-Sheng

2018-03-22

Spark-assisted chemical engraving (SACE) is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool electrode was pre-pressured on the quartz glass surface to feed the electrode that was in contact with the machining surface of the quartz glass. In situ image acquisition and analysis of the SACE drilling processes were used to analyze the captured image of the state of the spark discharge at the tip and sidewall of the electrode. The results indicated an association between the accumulative size of the SACE-induced spark area and deepness of the hole. The results indicated that the evaluated depths of the SACE-machined holes were a proportional function of the accumulative spark size with a high degree of correlation. The study proposes an innovative computer vision-based method to estimate the deepness and status of SACE-drilled holes in real time.

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.

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.

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...

Production Engineering Program to Develop Improved Mass-Production Process for M42/M46 Grenade Bodies

DTIC Science & Technology

1978-03-01

J16 Photograph 3 Knurling Tool Installed in Machine . . ....... 16 Photograph 4 Shrapnel Pattern Being Knurled Into M42 Grenade Cylinder...body Fenn mill embossing rolls. Roehlen was awarded a cuxiu**L am’i labricated a knurling tool for use in the modified Tesker thread-rolling machine ...automatic grinding machine . IKratz-Wilde was not successful in developing tooling to produce domes to the inertia-welded assembly design. (See Figure

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.

ORACLE (Oversight of Resources and Capability for Logistics Effectiveness) and Requirements Forecasting. Volume 3. Predicting the Peacetime Spares Requirements.

DTIC Science & Technology

1988-05-01

Shearing Machines WR/MMI DG 3446 Forging Machinery and Hammers WR/MMI DG 3447 Wire and Metal Ribbon Forming Machines WR/MMI DG 3448 Riveting Machines ...R/MN1I DG 3449 Miscellaneous Secondary Metal Forming & Cutting WR/MMI DG Machinery 3450 Machine Tools, Portable WR/MMI DG 3455 Cutting Tools for...Secondary Metalworking Machinery WR/MMI DG WR 3465 Production Jigs, Fixtures and Templates WR/MMI DG WR 3470 Machine Shop Sets, Kits, and Outfits WR/MMI DG

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis

PubMed Central

Gong, Xiajing; Hu, Meng

2018-01-01

Abstract Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time‐to‐event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high‐dimensional data featured by a large number of predictor variables. Our results showed that ML‐based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high‐dimensional data. The prediction performances of ML‐based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML‐based methods provide a powerful tool for time‐to‐event analysis, with a built‐in capacity for high‐dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. PMID:29536640

Workshop on Aerospace Materials for Extreme Environments

DTIC Science & Technology

2009-12-01

Materials for Titanium Alloys Machining Ukraine Volodymyr Filipov Influence of Lattice Parameter Mismatch between Fibers and Matrix on Structure and...on your own 1:00 pm Alina Ievdokymova ZrBi2-Based Tool Materials for Titanium Alloys Machining 1:30 pm Donna Ballard and Don Weaver Processing of...C.K. Gren, T.P. Hanusa, "Deposition of Alumina From Dimethylaluminum Isopropoxide " Ken Sandhage D. Lipke, Y. Zhang, Y. Liu, B. Church, and K

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.

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.

Geometric improvement of electrochemical discharge micro-drilling using an ultrasonic-vibrated electrolyte

NASA Astrophysics Data System (ADS)

Han, Min-Seop; Min, Byung-Kwon; Lee, Sang Jo

2009-06-01

Electrochemical discharge machining (ECDM) is a spark-based micromachining method especially suitable for the fabrication of various microstructures on nonconductive materials, such as glass and some engineering ceramics. However, since the spark discharge frequency is drastically reduced as the machining depth increases ECDM microhole drilling has confronted difficulty in achieving uniform geometry for machined holes. One of the primary reasons for this is the difficulty of sustaining an adequate electrolyte flow in the narrow gap between the tool and the workpiece, which results in a widened taper at the hole entrance, as well as a significant reduction of the machining depth. In this paper, ultrasonic electrolyte vibration was used to enhance the machining depth of the ECDM drilling process by assuring an adequate electrolyte flow, thus helping to maintain consistent spark generation. Moreover, the stability of the gas film formation, as well as the surface quality of the hole entrance, was improved with the aid of a side-insulated electrode and a pulse-power generator. The side-insulated electrode prevented stray electrolysis and concentrated the spark discharge at the tool tip, while the pulse voltage reduced thermal damage to the workpiece surface by introducing a periodic pulse-off time. Microholes were fabricated in order to investigate the effects of ultrasonic assistance on the overcut and machining depth of the holes. The experimental results demonstrated that the possibility of consistent spark generation and the machinability of microholes were simultaneously enhanced.

A Modelling Method of Bolt Joints Based on Basic Characteristic Parameters of Joint Surfaces

NASA Astrophysics Data System (ADS)

Yuansheng, Li; Guangpeng, Zhang; Zhen, Zhang; Ping, Wang

2018-02-01

Bolt joints are common in machine tools and have a direct impact on the overall performance of the tools. Therefore, the understanding of bolt joint characteristics is essential for improving machine design and assembly. Firstly, According to the experimental data obtained from the experiment, the stiffness curve formula was fitted. Secondly, a finite element model of unit bolt joints such as bolt flange joints, bolt head joints, and thread joints was constructed, and lastly the stiffness parameters of joint surfaces were implemented in the model by the secondary development of ABAQUS. The finite element model of the bolt joint established by this method can simulate the contact state very well.

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 ...

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.

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.

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.

GeoDeepDive: Towards a Machine Reading-Ready Digital Library and Information Integration Resource

NASA Astrophysics Data System (ADS)

Husson, J. M.; Peters, S. E.; Livny, M.; Ross, I.

2015-12-01

Recent developments in machine reading and learning approaches to text and data mining hold considerable promise for accelerating the pace and quality of literature-based data synthesis, but these advances have outpaced even basic levels of access to the published literature. For many geoscience domains, particularly those based on physical samples and field-based descriptions, this limitation is significant. Here we describe a general infrastructure to support published literature-based machine reading and learning approaches to information integration and knowledge base creation. This infrastructure supports rate-controlled automated fetching of original documents, along with full bibliographic citation metadata, from remote servers, the secure storage of original documents, and the utilization of considerable high-throughput computing resources for the pre-processing of these documents by optical character recognition, natural language parsing, and other document annotation and parsing software tools. New tools and versions of existing tools can be automatically deployed against original documents when they are made available. The products of these tools (text/XML files) are managed by MongoDB and are available for use in data extraction applications. Basic search and discovery functionality is provided by ElasticSearch, which is used to identify documents of potential relevance to a given data extraction task. Relevant files derived from the original documents are then combined into basic starting points for application building; these starting points are kept up-to-date as new relevant documents are incorporated into the digital library. Currently, our digital library stores contains more than 360K documents supplied by Elsevier and the USGS and we are actively seeking additional content providers. By focusing on building a dependable infrastructure to support the retrieval, storage, and pre-processing of published content, we are establishing a foundation for complex, and continually improving, information integration and data extraction applications. We have developed one such application, which we present as an example, and invite new collaborations to develop other such applications.

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.

Piezoelectric shunt damping of a circular saw blade with autonomous power supply for noise and vibration reduction

NASA Astrophysics Data System (ADS)

Pohl, Martin; Rose, Michael

2016-01-01

Circular saws are widespread tools for machining metal, wood or even ceramics. Due to the thin blade and excitation by the workpiece contact of the cutting edges, circular saws are prone to vibration and intense noise emission. Damping the blade will lower the hearing protection requirements of the users and possibly increase precision. Therefore a new damping concept for circular saw blades is presented in this paper. It is based on negative capacitance shunted piezoelectric transducers which are applied to the saw blade core. The required energy for the electronics is harvested from the rotation by a generator, so that no change of the machine tool is required. All components are integrated into an autonomous saw tool. Finally, the system is experimentally investigated without rotation, in idling and in cutting condition in a circular saw test stand in the Institute for Machine Tools and Production Engineering (IWF) at TU Braunschweig. The experimental investigation shows a good reduction of the vibration amplitude over a wide frequency range in the non-rotating condition. When rotating, the damping effect is lower and limited to some narrow frequency bands. The proposed reason for the reduced damping effect in rotating condition consists in the saturation of the electronic circuits due to the limited supply voltage capabilities.

Neural networks with fuzzy Petri nets for modeling a machining process

NASA Astrophysics Data System (ADS)

Hanna, Moheb M.

1998-03-01

The paper presents an intelligent architecture based a feedforward neural network with fuzzy Petri nets for modeling product quality in a CNC machining center. It discusses how the proposed architecture can be used for modeling, monitoring and control a product quality specification such as surface roughness. The surface roughness represents the output quality specification manufactured by a CNC machining center as a result of a milling process. The neural network approach employed the selected input parameters which defined by the machine operator via the CNC code. The fuzzy Petri nets approach utilized the exact input milling parameters, such as spindle speed, feed rate, tool diameter and coolant (off/on), which can be obtained via the machine or sensors system. An aim of the proposed architecture is to model the demanded quality of surface roughness as high, medium or low.

Bidding-based autonomous process planning and scheduling

NASA Astrophysics Data System (ADS)

Gu, Peihua; Balasubramanian, Sivaram; Norrie, Douglas H.

1995-08-01

Improving productivity through computer integrated manufacturing systems (CIMS) and concurrent engineering requires that the islands of automation in an enterprise be completely integrated. The first step in this direction is to integrate design, process planning, and scheduling. This can be achieved through a bidding-based process planning approach. The product is represented in a STEP model with detailed design and administrative information including design specifications, batch size, and due dates. Upon arrival at the manufacturing facility, the product registered in the shop floor manager which is essentially a coordinating agent. The shop floor manager broadcasts the product's requirements to the machines. The shop contains autonomous machines that have knowledge about their functionality, capabilities, tooling, and schedule. Each machine has its own process planner and responds to the product's request in a different way that is consistent with its capabilities and capacities. When more than one machine offers certain process(es) for the same requirements, they enter into negotiation. Based on processing time, due date, and cost, one of the machines wins the contract. The successful machine updates its schedule and advises the product to request raw material for processing. The concept was implemented using a multi-agent system with the task decomposition and planning achieved through contract nets. The examples are included to illustrate the approach.

OPMILL - MICRO COMPUTER PROGRAMMING ENVIRONMENT FOR CNC MILLING MACHINES THREE AXIS EQUATION PLOTTING CAPABILITIES

NASA Technical Reports Server (NTRS)

Ray, R. B.

1994-01-01

OPMILL is a computer operating system for a Kearney and Trecker milling machine that provides a fast and easy way to program machine part manufacture with an IBM compatible PC. The program gives the machinist an "equation plotter" feature which plots any set of equations that define axis moves (up to three axes simultaneously) and converts those equations to a machine milling program that will move a cutter along a defined path. Other supported functions include: drill with peck, bolt circle, tap, mill arc, quarter circle, circle, circle 2 pass, frame, frame 2 pass, rotary frame, pocket, loop and repeat, and copy blocks. The system includes a tool manager that can handle up to 25 tools and automatically adjusts tool length for each tool. It will display all tool information and stop the milling machine at the appropriate time. Information for the program is entered via a series of menus and compiled to the Kearney and Trecker format. The program can then be loaded into the milling machine, the tool path graphically displayed, and tool change information or the program in Kearney and Trecker format viewed. The program has a complete file handling utility that allows the user to load the program into memory from the hard disk, save the program to the disk with comments, view directories, merge a program on the disk with one in memory, save a portion of a program in memory, and change directories. OPMILL was developed on an IBM PS/2 running DOS 3.3 with 1 MB of RAM. OPMILL was written for an IBM PC or compatible 8088 or 80286 machine connected via an RS-232 port to a Kearney and Trecker Data Mill 700/C Control milling machine. It requires a "D:" drive (fixed-disk or virtual), a browse or text display utility, and an EGA or better display. Users wishing to modify and recompile the source code will also need Turbo BASIC, Turbo C, and Crescent Software's QuickPak for Turbo BASIC. IBM PC and IBM PS/2 are registered trademarks of International Business Machines. Turbo BASIC and Turbo C are trademarks of Borland International.

Temperature Measurement and Numerical Prediction in Machining Inconel 718

PubMed Central

Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-01-01

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning. PMID:28665312

HUMAN ENGINEERING FOR AN EFFECTIVE AIR-NAVIGATION AND TRAFFIC-CONTROL SYSTEM, AND APPENDIXES 1 THRU 3

DTIC Science & Technology

1951-03-14

human "We have been very much occupied In perfect. engineering to the improvement of the air-navigation ing the machines and the tools which the...a man-machine system which will ever, if he were only considered as an instrument, yield optimal results in the way of efficiency and a tool , a motor...operation of machines and equipment and system development, which will permit tools , the emphasis has been upon the adjustment of an orderly and

Tool wear mechanisms in turning titanium-aluminum-vanadium using tungsten carbide and polycrystalline diamond inserts

NASA Astrophysics Data System (ADS)

Schrock, David James

The objective of this work is to identify some of the tool wear mechanisms at the material level for the machining of titanium and to provide some understanding of these mechanisms for use in physics based tool wear models. Turning experiments were conducted at cutting speeds of 61m/min, 91m/min, and 122m/min on Ti-6Al-4V, an alloy of titanium, using two different grades of tungsten carbide cutting inserts and one grade of polycrystalline diamond inserts. Three-dimensional wear data and two-dimensional wear profiles of the rake face were generated using Confocal Laser Scanning Microscopy to quantify the tool wear mechanisms. Additionally, the microstructure of the deformed work material (chip) and un-deformed parent material (work piece) were studied using Orientation Imaging Microscopy (OIM). Observations from tool wear studies on the PCD inserts revealed the presence of two fundamentally different wear mechanisms operating at the different cutting speeds. Microstructural analyses of the chip and the work material showed phase dependent tool wear mechanisms for machining titanium. There is a high likelihood of phase change occurring in the work material during machining, with a transformation from the alpha phase to the beta phase. The observed dramatic increase in wear is attributed to a combination of increased diffusivity in the beta phase of the titanium alloy in conjunction with a higher degree of recrystallization of the prior beta phase upon cooling. Results of other observations such as the influence of carbide grain size on tool wear are also discussed.

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.

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.

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.

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.

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.

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…

Predictive models to assess risk of type 2 diabetes, hypertension and comorbidity: machine-learning algorithms and validation using national health data from Kuwait--a cohort study.

PubMed

Farran, Bassam; Channanath, Arshad Mohamed; Behbehani, Kazem; Thanaraj, Thangavel Alphonse

2013-05-14

We build classification models and risk assessment tools for diabetes, hypertension and comorbidity using machine-learning algorithms on data from Kuwait. We model the increased proneness in diabetic patients to develop hypertension and vice versa. We ascertain the importance of ethnicity (and natives vs expatriate migrants) and of using regional data in risk assessment. Retrospective cohort study. Four machine-learning techniques were used: logistic regression, k-nearest neighbours (k-NN), multifactor dimensionality reduction and support vector machines. The study uses fivefold cross validation to obtain generalisation accuracies and errors. Kuwait Health Network (KHN) that integrates data from primary health centres and hospitals in Kuwait. 270 172 hospital visitors (of which, 89 858 are diabetic, 58 745 hypertensive and 30 522 comorbid) comprising Kuwaiti natives, Asian and Arab expatriates. Incident type 2 diabetes, hypertension and comorbidity. Classification accuracies of >85% (for diabetes) and >90% (for hypertension) are achieved using only simple non-laboratory-based parameters. Risk assessment tools based on k-NN classification models are able to assign 'high' risk to 75% of diabetic patients and to 94% of hypertensive patients. Only 5% of diabetic patients are seen assigned 'low' risk. Asian-specific models and assessments perform even better. Pathological conditions of diabetes in the general population or in hypertensive population and those of hypertension are modelled. Two-stage aggregate classification models and risk assessment tools, built combining both the component models on diabetes (or on hypertension), perform better than individual models. Data on diabetes, hypertension and comorbidity from the cosmopolitan State of Kuwait are available for the first time. This enabled us to apply four different case-control models to assess risks. These tools aid in the preliminary non-intrusive assessment of the population. Ethnicity is seen significant to the predictive models. Risk assessments need to be developed using regional data as we demonstrate the applicability of the American Diabetes Association online calculator on data from Kuwait.

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.

Aerospace Mechanisms Symposium (22nd) Held at Hampton, Virginia on 4-6 May 1988.

DTIC Science & Technology

1988-05-06

monitoring is accomplished by a pressure transducer located near the hole drilled through the vessel wall between seals. A lip is machined on the...are presented and a design example involving a machine tool metrology bench is given. Design goals included thousandfold strain attenuation in the...systems such as a metrology bench, etc. These bodies must be supported. Six degrees of freedom must be fixed, but if the base upon which they are

Dynamic high-speed acquisition system design of transmission error with USB based on LabVIEW and FPGA

NASA Astrophysics Data System (ADS)

Zheng, Yong; Chen, Yan

2013-10-01

To realize the design of dynamic acquisition system for real-time detection of transmission chain error is very important to improve the machining accuracy of machine tool. In this paper, the USB controller and FPGA is used for hardware platform design, combined with LabVIEW to design user applications, NI-VISA is taken for develop USB drivers, and ultimately achieve the dynamic acquisition system design of transmission error

Design and Construction Multi Output Power Transmition with Single Prime Mover on Agricultural Products Machine

NASA Astrophysics Data System (ADS)

Koten, V. K.; Tanamal, C. E.

2017-03-01

Manufacturing agricultural products by the farmers, people or person who involve in medium industry, small industry, and households industry still be done in separately. Although the power on primemover is enough, in operations, primemover was only to move one of several agricultural products machine. This study attempts to design and construct power transmition multi output with single primemover; a single construction that allows primemover move some agricultur products machine in the same or not. This study begins with the determination of production capacity and the power to destroy products, the determination of resources and rotation, normalization of resources and rotation, the determination of the type material used, the size determination of each machine elements, construction machine elements, and assemble machine elements into a construction multi output power transmition with single primemover on agricultural products machine. The results show that with a input normalization 4 PK (2984 Watt), rotation 2000 rpm, the strength of material 60 kg/mm2, and several operating consideration, thus obtained size of machine elements through calculation. Based on the size, the machine elements is made through the use of some machine tools and assembled to form a multi output power transmition with single primemover.

The Detection of Malingering: A New Tool to Identify Made-Up Depression.

PubMed

Monaro, Merylin; Toncini, Andrea; Ferracuti, Stefano; Tessari, Gianmarco; Vaccaro, Maria G; De Fazio, Pasquale; Pigato, Giorgio; Meneghel, Tiziano; Scarpazza, Cristina; Sartori, Giuseppe

2018-01-01

Major depression is a high-prevalence mental disease with major socio-economic impact, for both the direct and the indirect costs. Major depression symptoms can be faked or exaggerated in order to obtain economic compensation from insurance companies. Critically, depression is potentially easily malingered, as the symptoms that characterize this psychiatric disorder are not difficult to emulate. Although some tools to assess malingering of psychiatric conditions are already available, they are principally based on self-reporting and are thus easily faked. In this paper, we propose a new method to automatically detect the simulation of depression, which is based on the analysis of mouse movements while the patient is engaged in a double-choice computerized task, responding to simple and complex questions about depressive symptoms. This tool clearly has a key advantage over the other tools: the kinematic movement is not consciously controllable by the subjects, and thus it is almost impossible to deceive. Two groups of subjects were recruited for the study. The first one, which was used to train different machine-learning algorithms, comprises 60 subjects (20 depressed patients and 40 healthy volunteers); the second one, which was used to test the machine-learning models, comprises 27 subjects (9 depressed patients and 18 healthy volunteers). In both groups, the healthy volunteers were randomly assigned to the liars and truth-tellers group. Machine-learning models were trained on mouse dynamics features, which were collected during the subject response, and on the number of symptoms reported by participants. Statistical results demonstrated that individuals that malingered depression reported a higher number of depressive and non-depressive symptoms than depressed participants, whereas individuals suffering from depression took more time to perform the mouse-based tasks compared to both truth-tellers and liars. Machine-learning models reached a classification accuracy up to 96% in distinguishing liars from depressed patients and truth-tellers. Despite this, the data are not conclusive, as the accuracy of the algorithm has not been compared with the accuracy of the clinicians; this study presents a possible useful method that is worth further investigation.

Experimental investigations on cryogenic cooling by liquid nitrogen in the end milling of hardened steel

NASA Astrophysics Data System (ADS)

Ravi, S.; Pradeep Kumar, M.

2011-09-01

Milling of hardened steel generates excessive heat during the chip formation process, which increases the temperature of cutting tool and accelerates tool wear. Application of conventional cutting fluid in milling process may not effectively control the heat generation also it has inherent health and environmental problems. To minimize health hazard and environmental problems caused by using conventional cutting fluid, a cryogenic cooling set up is developed to cool tool-chip interface using liquid nitrogen (LN 2). This paper presents results on the effect of LN 2 as a coolant on machinability of hardened AISI H13 tool steel for varying cutting speed in the range of 75-125 m/min during end milling with PVD TiAlN coated carbide inserts at a constant feed rate. The results show that machining with LN 2 lowers cutting temperature, tool flank wear, surface roughness and cutting forces as compared with dry and wet machining. With LN 2 cooling, it has been found that the cutting temperature was reduced by 57-60% and 37-42%; the tool flank wear was reduced by 29-34% and 10-12%; the surface roughness was decreased by 33-40% and 25-29% compared to dry and wet machining. The cutting forces also decreased moderately compared to dry and wet machining. This can be attributed to the fact that LN 2 machining provides better cooling and lubrication through substantial reduction in the cutting zone temperature.

Cost minimizing of cutting process for CNC thermal and water-jet machines

NASA Astrophysics Data System (ADS)

Tavaeva, Anastasia; Kurennov, Dmitry

2015-11-01

This paper deals with optimization problem of cutting process for CNC thermal and water-jet machines. The accuracy of objective function parameters calculation for optimization problem is investigated. This paper shows that working tool path speed is not constant value. One depends on some parameters that are described in this paper. The relations of working tool path speed depending on the numbers of NC programs frames, length of straight cut, configuration part are presented. Based on received results the correction coefficients for working tool speed are defined. Additionally the optimization problem may be solved by using mathematical model. Model takes into account the additional restrictions of thermal cutting (choice of piercing and output tool point, precedence condition, thermal deformations). At the second part of paper the non-standard cutting techniques are considered. Ones may lead to minimizing of cutting cost and time compared with standard cutting techniques. This paper considers the effectiveness of non-standard cutting techniques application. At the end of the paper the future research works are indicated.

[A prediction model for the activity of insecticidal crystal proteins from Bacillus thuringiensis based on support vector machine].

PubMed

Lin, Yi; Cai, Fu-Ying; Zhang, Guang-Ya

2007-01-01

A quantitative structure-property relationship (QSPR) model in terms of amino acid composition and the activity of Bacillus thuringiensis insecticidal crystal proteins was established. Support vector machine (SVM) is a novel general machine-learning tool based on the structural risk minimization principle that exhibits good generalization when fault samples are few; it is especially suitable for classification, forecasting, and estimation in cases where small amounts of samples are involved such as fault diagnosis; however, some parameters of SVM are selected based on the experience of the operator, which has led to decreased efficiency of SVM in practical application. The uniform design (UD) method was applied to optimize the running parameters of SVM. It was found that the average accuracy rate approached 73% when the penalty factor was 0.01, the epsilon 0.2, the gamma 0.05, and the range 0.5. The results indicated that UD might be used an effective method to optimize the parameters of SVM and SVM and could be used as an alternative powerful modeling tool for QSPR studies of the activity of Bacillus thuringiensis (Bt) insecticidal crystal proteins. Therefore, a novel method for predicting the insecticidal activity of Bt insecticidal crystal proteins was proposed by the authors of this study.

System technology for laser-assisted milling with tool integrated optics

NASA Astrophysics Data System (ADS)

Hermani, Jan-Patrick; Emonts, Michael; Brecher, Christian

2013-02-01

High strength metal alloys and ceramics offer a huge potential for increased efficiency (e. g. in engine components for aerospace or components for gas turbines). However, mass application is still hampered by cost- and time-consuming end-machining due to long processing times and high tool wear. Laser-induced heating shortly before machining can reduce the material strength and improve machinability significantly. The Fraunhofer IPT has developed and successfully realized a new approach for laser-assisted milling with spindle and tool integrated, co-rotating optics. The novel optical system inside the tool consists of one deflection prism to position the laser spot in front of the cutting insert and one focusing lens. Using a fiber laser with high beam quality the laser spot diameter can be precisely adjusted to the chip size. A high dynamic adaption of the laser power signal according to the engagement condition of the cutting tool was realized in order not to irradiate already machined work piece material. During the tool engagement the laser power is controlled in proportion to the current material removal rate, which has to be calculated continuously. The needed geometric values are generated by a CAD/CAM program and converted into a laser power signal by a real-time controller. The developed milling tool with integrated optics and the algorithm for laser power control enable a multi-axis laser-assisted machining of complex parts.

An Introduction to Intelligent Processing Programs Developed by the Air Force Manufacturing Technology Directorate

NASA Technical Reports Server (NTRS)

Sampson, Paul G.; Sny, Linda C.

1992-01-01

The Air Force has numerous on-going manufacturing and integration development programs (machine tools, composites, metals, assembly, and electronics) which are instrumental in improving productivity in the aerospace industry, but more importantly, have identified strategies and technologies required for the integration of advanced processing equipment. An introduction to four current Air Force Manufacturing Technology Directorate (ManTech) manufacturing areas is provided. Research is being carried out in the following areas: (1) machining initiatives for aerospace subcontractors which provide for advanced technology and innovative manufacturing strategies to increase the capabilities of small shops; (2) innovative approaches to advance machine tool products and manufacturing processes; (3) innovative approaches to advance sensors for process control in machine tools; and (4) efforts currently underway to develop, with the support of industry, the Next Generation Workstation/Machine Controller (Low-End Controller Task).

Research on the processing technology of elongated holes based on rotary ultrasonic drilling

NASA Astrophysics Data System (ADS)

Tong, Yi; Chen, Jianhua; Sun, Lipeng; Yu, Xin; Wang, Xin

2014-08-01

The optical glass is hard, brittle and difficult to process. Based on the method of rotating ultrasonic drilling, the study of single factor on drilling elongated holes was made in optical glass. The processing equipment was DAMA ultrasonic machine, and the machining tools were electroplated with diamond. Through the detection and analysis on the processing quality and surface roughness, the process parameters (the spindle speed, amplitude, feed rate) of rotary ultrasonic drilling were researched, and the influence of processing parameters on surface roughness was obtained, which will provide reference and basis for the actual processing.

FTAPE: A fault injection tool to measure fault tolerance

NASA Technical Reports Server (NTRS)

Tsai, Timothy K.; Iyer, Ravishankar K.

1995-01-01

The paper introduces FTAPE (Fault Tolerance And Performance Evaluator), a tool that can be used to compare fault-tolerant computers. The tool combines system-wide fault injection with a controllable workload. A workload generator is used to create high stress conditions for the machine. Faults are injected based on this workload activity in order to ensure a high level of fault propagation. The errors/fault ratio and performance degradation are presented as measures of fault tolerance.

Virtualization for Cost-Effective Teaching of Assembly Language Programming

ERIC Educational Resources Information Center

Cadenas, José O.; Sherratt, R. Simon; Howlett, Des; Guy, Chris G.; Lundqvist, Karsten O.

2015-01-01

This paper describes a virtual system that emulates an ARM-based processor machine, created to replace a traditional hardware-based system for teaching assembly language. The virtual system proposed here integrates, in a single environment, all the development tools necessary to deliver introductory or advanced courses on modern assembly language…

Fabrication of micro-lens array on convex surface by meaning of micro-milling

NASA Astrophysics Data System (ADS)

Zhang, Peng; Du, Yunlong; Wang, Bo; Shan, Debin

2014-08-01

In order to develop the application of the micro-milling technology, and to fabricate ultra-precision optical surface with complex microstructure, in this paper, the primary experimental research on micro-milling complex microstructure array is carried out. A complex microstructure array surface with vary parameters is designed, and the mathematic model of the surface is set up and simulated. For the fabrication of the designed microstructure array surface, a micro three-axis ultra-precision milling machine tool is developed, aerostatic guideway drove directly by linear motor is adopted in order to guarantee the enough stiffness of the machine, and novel numerical control strategy with linear encoders of 5nm resolution used as the feedback of the control system is employed to ensure the extremely high motion control accuracy. With the help of CAD/CAM technology, convex micro lens array on convex spherical surface with different scales on material of polyvinyl chloride (PVC) and pure copper is fabricated using micro tungsten carbide ball end milling tool based on the ultra-precision micro-milling machine. Excellent nanometer-level micro-movement performance of the axis is proved by motion control experiment. The fabrication is nearly as the same as the design, the characteristic scale of the microstructure is less than 200μm and the accuracy is better than 1μm. It prove that ultra-precision micro-milling technology based on micro ultra-precision machine tool is a suitable and optional method for micro manufacture of microstructure array surface on different kinds of materials, and with the development of micro milling cutter, ultraprecision micro-milling complex microstructure surface will be achieved in future.

Simulation as a planning tool for job-shop production environment

NASA Astrophysics Data System (ADS)

Maram, Venkataramana; Nawawi, Mohd Kamal Bin Mohd; Rahman, Syariza Abdul; Sultan, Sultan Juma

2015-12-01

In this paper, we made an attempt to use discrete event simulation software ARENA® as a planning tool for job shop production environment. We considered job shop produces three types of Jigs with different sequence of operations to study and improve shop floor performance. The sole purpose of the study is to identifying options to improve machines utilization, reducing job waiting times at bottleneck machines. First, the performance of the existing system was evaluated by using ARENA®. Then identified improvement opportunities by analyzing base system results. Second, updated the model with most economical options. The proposed new system outperforms with that of the current base system by 816% improvement in delay times at paint shop by increase 2 to 3 and Jig cycle time reduces by Jig1 92%, Jig2 65% and Jig3 41% and hence new proposal was recommended.

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.

Considerations on the construction of a Powder Bed Fusion platform for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Andersen, Sebastian Aagaard; Nielsen, Karl-Emil; Pedersen, David Bue; Nielsen, Jakob Skov

As the demand for moulds and other tools becomes increasingly specific and complex, an additive manufacturing approach to production is making its way to the industry through laser based consolidation of metal powder particles by a method known as powder bed fusion. This paper concerns a variety of design choices facilitating the development of an experimental powder bed fusion machine tool, capable of manufacturing metal parts with strength matching that of conventional manufactured parts and a complexity surpassing that of subtractive processes. To understand the different mechanisms acting within such an experimental machine tool, a fully open and customizable rig is constructed. Emphasizing modularity in the rig, allows alternation of lasers, scanner systems, optical elements, powder deposition, layer height, temperature, atmosphere, and powder type. Through a custom-made software platform, control of the process is achieved, which extends into a graphical user interface, easing adjustment of process parameters and the job file generation.

Method and system for assembling miniaturized devices

DOEpatents

Montesanti, Richard C.; Klingmann, Jeffrey L.; Seugling, Richard M.

2013-03-12

An apparatus for assembling a miniaturized device includes a manipulator system including six manipulators operable to position and orient components of the miniaturized device with submicron precision and micron-level accuracy. The manipulator system includes a first plurality of motorized axes, a second plurality of manual axes, and force and torque and sensors. Each of the six manipulators includes at least one translation stage, at least one rotation stage, tooling attached to the at least one translation stage or the at least one rotation stage, and an attachment mechanism disposed at a distal end of the tooling and operable to attach at least a portion of the miniaturized device to the tooling. The apparatus also includes an optical coordinate-measuring machine (OCMM) including a machine-vision system, a laser-based distance-measuring probe, and a touch probe. The apparatus also includes an operator control system coupled to the manipulator system and the OCMM.

Integrated verification and testing system (IVTS) for HAL/S programs

NASA Technical Reports Server (NTRS)

Senn, E. H.; Ames, K. R.; Smith, K. A.

1983-01-01

The IVTS is a large software system designed to support user-controlled verification analysis and testing activities for programs written in the HAL/S language. The system is composed of a user interface and user command language, analysis tools and an organized data base of host system files. The analysis tools are of four major types: (1) static analysis, (2) symbolic execution, (3) dynamic analysis (testing), and (4) documentation enhancement. The IVTS requires a split HAL/S compiler, divided at the natural separation point between the parser/lexical analyzer phase and the target machine code generator phase. The IVTS uses the internal program form (HALMAT) between these two phases as primary input for the analysis tools. The dynamic analysis component requires some way to 'execute' the object HAL/S program. The execution medium may be an interpretive simulation or an actual host or target machine.

Reducing forces during drilling brittle hard materials by using ultrasonic and variation of coolant

NASA Astrophysics Data System (ADS)

Schopf, C.; Rascher, R.

2016-11-01

The process of ultrasonic machining is especially used for brittle hard materials as the additional ultrasonic vibration of the tool at high frequencies and low amplitudes acts like a hammer on the surface. With this technology it is possible to drill holes with lower forces, therefor the machining can be done faster and the worktime is much less than conventionally. A three-axis dynamometer was used to measure the forces, which act between the tool and the sample part. A focus is set on the sharpness of the tool. The results of a test series are based on the Sauer Ultrasonic Grinding Centre. On the same machine it is possible to drill holes in the conventional way. Additional to the ultasonic Input the type an concentration of coolant is important for the Drilling-force. In the test there were three different coolant and three different concentrations tested. The combination of ultrasonic vibration and the right coolant and concentration is the best way to reduce the Forces. Another positive effect is, that lower drilling-forces produce smaller chipping on the edge of the hole. The way to reduce the forces and chipping is the main issue of this paper.

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.

FwWebViewPlus: integration of web technologies into WinCC OA based Human-Machine Interfaces at CERN

NASA Astrophysics Data System (ADS)

Golonka, Piotr; Fabian, Wojciech; Gonzalez-Berges, Manuel; Jasiun, Piotr; Varela-Rodriguez, Fernando

2014-06-01

The rapid growth in popularity of web applications gives rise to a plethora of reusable graphical components, such as Google Chart Tools and JQuery Sparklines, implemented in JavaScript and run inside a web browser. In the paper we describe the tool that allows for seamless integration of web-based widgets into WinCC Open Architecture, the SCADA system used commonly at CERN to build complex Human-Machine Interfaces. Reuse of widely available widget libraries and pushing the development efforts to a higher abstraction layer based on a scripting language allow for significant reduction in maintenance of the code in multi-platform environments compared to those currently used in C++ visualization plugins. Adequately designed interfaces allow for rapid integration of new web widgets into WinCC OA. At the same time, the mechanisms familiar to HMI developers are preserved, making the use of new widgets "native". Perspectives for further integration between the realms of WinCC OA and Web development are also discussed.

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.

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.

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

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

PubMed

Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

2016-01-01

One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science

PubMed Central

Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

2016-01-01

One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

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.

Research Results Of Stress-Strain State Of Cutting Tool When Aviation Materials Turning

NASA Astrophysics Data System (ADS)

Serebrennikova, A. G.; Nikolaeva, E. P.; Savilov, A. V.; Timofeev, S. A.; Pyatykh, A. S.

2018-01-01

Titanium alloys and stainless steels are hard-to-machine of all the machining types. Cutting edge state of turning tool after machining titanium and high-strength aluminium alloys and corrosion-resistant high-alloy steel has been studied. Cutting forces and chip contact arears with the rake surface of cutter has been measured. The relationship of cutting forces and residual stresses are shown. Cutting forces and residual stresses vs value of cutting tool rake angle relation were obtained. Measurements of residual stresses were performed by x-ray diffraction.

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.

Developing Local Board of Health Guidelines to Promote Healthy Food Access — King County, Washington, 2010–2012

PubMed Central

Johnson, Donna B.; Krieger, James; MacDougall, Erin; Payne, Elizabeth; Chan, Nadine L.

2015-01-01

Policies that change environments are important tools for preventing chronic diseases, including obesity. Boards of health often have authority to adopt such policies, but few do so. This study assesses 1) how one local board of health developed a policy approach for healthy food access through vending machine guidelines (rather than regulations) and 2) the impact of the approach. Using a case study design guided by “three streams” policy theory and RE-AIM, we analyzed data from a focus group, interviews, and policy documents. The guidelines effectively supported institutional policy development in several settings. Recognition of the problem of chronic disease and the policy solution of vending machine guidelines created an opening for the board to influence nutrition environments. Institutions identified a need for support in adopting vending machine policies. Communities could benefit from the study board’s approach to using nonregulatory evidence-based guidelines as a policy tool. PMID:25927606

Scheduling job shop - A case study

NASA Astrophysics Data System (ADS)

Abas, M.; Abbas, A.; Khan, W. A.

2016-08-01

The scheduling in job shop is important for efficient utilization of machines in the manufacturing industry. There are number of algorithms available for scheduling of jobs which depend on machines tools, indirect consumables and jobs which are to be processed. In this paper a case study is presented for scheduling of jobs when parts are treated on available machines. Through time and motion study setup time and operation time are measured as total processing time for variety of products having different manufacturing processes. Based on due dates different level of priority are assigned to the jobs and the jobs are scheduled on the basis of priority. In view of the measured processing time, the times for processing of some new jobs are estimated and for efficient utilization of the machines available an algorithm is proposed and validated.

The Tool Life of Ball Nose end Mill Depending on the Different Types of Ramping

NASA Astrophysics Data System (ADS)

Vopát, Tomáš; Peterka, Jozef; Kováč, Martin

2014-12-01

The article deals with the cutting tool wear measurement process and tool life of ball nose end mill depending on upward ramping and downward ramping. The aim was to determine and compare the wear (tool life) of ball nose end mill for different types of copy milling operations, as well as to specify particular steps of the measurement process. In addition, we examined and observed cutter contact areas of ball nose end mill with machined material. For tool life test, DMG DMU 85 monoBLOCK 5-axis CNC milling machine was used. In the experiment, cutting speed, feed rate, axial depth of cut and radial depth of cut were not changed. The cutting tool wear was measured on Zoller Genius 3s universal measuring machine. The results show different tool life of ball nose end mills depending on the copy milling strategy.

Quantification of microscopic surface features of single point diamond turned optics with subsequent chemical polishing

NASA Astrophysics Data System (ADS)

Cardenas, Nelson; Kyrish, Matthew; Taylor, Daniel; Fraelich, Margaret; Lechuga, Oscar; Claytor, Richard; Claytor, Nelson

2015-03-01

Electro-Chemical Polishing is routinely used in the anodizing industry to achieve specular surface finishes of various metals products prior to anodizing. Electro-Chemical polishing functions by leveling the microscopic peaks and valleys of the substrate, thereby increasing specularity and reducing light scattering. The rate of attack is dependent of the physical characteristics (height, depth, and width) of the microscopic structures that constitute the surface finish. To prepare the sample, mechanical polishing such as buffing or grinding is typically required before etching. This type of mechanical polishing produces random microscopic structures at varying depths and widths, thus the electropolishing parameters are determined in an ad hoc basis. Alternatively, single point diamond turning offers excellent repeatability and highly specific control of substrate polishing parameters. While polishing, the diamond tool leaves behind an associated tool mark, which is related to the diamond tool geometry and machining parameters. Machine parameters such as tool cutting depth, speed and step over can be changed in situ, thus providing control of the spatial frequency of the microscopic structures characteristic of the surface topography of the substrate. By combining single point diamond turning with subsequent electro-chemical etching, ultra smooth polishing of both rotationally symmetric and free form mirrors and molds is possible. Additionally, machining parameters can be set to optimize post polishing for increased surface quality and reduced processing times. In this work, we present a study of substrate surface finish based on diamond turning tool mark spatial frequency with subsequent electro-chemical polishing.

Tool Integration Framework for Bio-Informatics

DTIC Science & Technology

2007-04-01

Java NetBeans [11] based Integrated Development Environment (IDE) for developing modules and packaging computational tools. The framework is extremely...integrate an Eclipse front-end for Desktop Integration. Eclipse was chosen over Netbeans owing to a higher acceptance, better infrastructure...5.0. This version of Dashboard ran with NetBeans IDE 3.6 requiring Java Runtime 1.4 on a machine with Windows XP. The toolchain is executed by

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...

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…

Translations on USSR Resources, Number 767.

DTIC Science & Technology

1978-01-19

photography and so on). The amount of data obtained as a result of additional surveys makes it possible to evaluate the intensity and configuration...machine tools , chemical products, refrigerators, as well as potatoes and products of livestock breeding. The Kazakh SSR made an enormous leap in its...of the fuel and water power resources of Georgia, Azerbaydzhan and Armenia. Petroleum, transport and electrical machine building, machine tool

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.

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.

Image understanding and the man-machine interface II; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

NASA Technical Reports Server (NTRS)

Barrett, Eamon B. (Editor); Pearson, James J. (Editor)

1989-01-01

Image understanding concepts and models, image understanding systems and applications, advanced digital processors and software tools, and advanced man-machine interfaces are among the topics discussed. Particular papers are presented on such topics as neural networks for computer vision, object-based segmentation and color recognition in multispectral images, the application of image algebra to image measurement and feature extraction, and the integration of modeling and graphics to create an infrared signal processing test bed.

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.

Fault detection in rotating machines with beamforming: Spatial visualization of diagnosis features

NASA Astrophysics Data System (ADS)

Cardenas Cabada, E.; Leclere, Q.; Antoni, J.; Hamzaoui, N.

2017-12-01

Rotating machines diagnosis is conventionally related to vibration analysis. Sensors are usually placed on the machine to gather information about its components. The recorded signals are then processed through a fault detection algorithm allowing the identification of the failing part. This paper proposes an acoustic-based diagnosis method. A microphone array is used to record the acoustic field radiated by the machine. The main advantage over vibration-based diagnosis is that the contact between the sensors and the machine is no longer required. Moreover, the application of acoustic imaging makes possible the identification of the sources of acoustic radiation on the machine surface. The display of information is then spatially continuous while the accelerometers only give it discrete. Beamforming provides the time-varying signals radiated by the machine as a function of space. Any fault detection tool can be applied to the beamforming output. Spectral kurtosis, which highlights the impulsiveness of a signal as function of frequency, is used in this study. The combination of spectral kurtosis with acoustic imaging makes possible the mapping of the impulsiveness as a function of space and frequency. The efficiency of this approach lays on the source separation in the spatial and frequency domains. These mappings make possible the localization of such impulsive sources. The faulty components of the machine have an impulsive behavior and thus will be highlighted on the mappings. The study presents experimental validations of the method on rotating machines.

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.

Functional specifications for AI software tools for electric power applications. Final report

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

Faught, W.S.

1985-08-01

The principle barrier to the introduction of artificial intelligence (AI) technology to the electric power industry has not been a lack of interest or appropriate problems, for the industry abounds in both. Like most others, however, the electric power industry lacks the personnel - knowledge engineers - with the special combination of training and skills AI programming demands. Conversely, very few AI specialists are conversant with electric power industry problems and applications. The recent availability of sophisticated AI programming environments is doing much to alleviate this shortage. These products provide a set of powerful and usable software tools that enablemore » even non-AI scientists to rapidly develop AI applications. The purpose of this project was to develop functional specifications for programming tools that, when integrated with existing general-purpose knowledge engineering tools, would expedite the production of AI applications for the electric power industry. Twelve potential applications, representative of major problem domains within the nuclear power industry, were analyzed in order to identify those tools that would be of greatest value in application development. Eight tools were specified, including facilities for power plant modeling, data base inquiry, simulation and machine-machine interface.« less

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.

Limitations Of The Current State Space Modelling Approach In Multistage Machining Processes Due To Operation Variations

NASA Astrophysics Data System (ADS)

Abellán-Nebot, J. V.; Liu, J.; Romero, F.

2009-11-01

The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.

Architecture For The Optimization Of A Machining Process In Real Time Through Rule-Based Expert System

NASA Astrophysics Data System (ADS)

Serrano, Rafael; González, Luis Carlos; Martín, Francisco Jesús

2009-11-01

Under the project SENSOR-IA which has had financial funding from the Order of Incentives to the Regional Technology Centers of the Counsil of Innovation, Science and Enterprise of Andalusia, an architecture for the optimization of a machining process in real time through rule-based expert system has been developed. The architecture consists of an acquisition system and sensor data processing engine (SATD) from an expert system (SE) rule-based which communicates with the SATD. The SE has been designed as an inference engine with an algorithm for effective action, using a modus ponens rule model of goal-oriented rules.The pilot test demonstrated that it is possible to govern in real time the machining process based on rules contained in a SE. The tests have been done with approximated rules. Future work includes an exhaustive collection of data with different tool materials and geometries in a database to extract more precise rules.

A Virtual Sensor for Online Fault Detection of Multitooth-Tools

PubMed Central

Bustillo, Andres; Correa, Maritza; Reñones, Anibal

2011-01-01

The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases. PMID:22163766

A virtual sensor for online fault detection of multitooth-tools.

PubMed

Bustillo, Andres; Correa, Maritza; Reñones, Anibal

2011-01-01

The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases.

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.

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 being carried away by the rubbing action of the chips -- this left behind a smooth crater surface predominantly of tungsten and cobalt as observed from EDS analysis. Also, at high surface speeds, carbon from the tool was found diffused into the adhered titanium layer to form a titanium carbide (TiC) boundary layer -- this was observed as instances of TiC build-up on the tool edge from EDS analysis. A complex wear mechanism interaction was thus observed, i.e., titanium adhered on top of an earlier worn out crater trough, additional carbon diffused into this adhered titanium layer to create a more stable boundary layer (which could limit diffusion-rates on saturation), and then all were further worn away by dissolution wear as temperatures increased. At low and medium feeds, notch discoloration was observed -- this was detected to be carbon from EDS analysis, suggesting that it was deposited from the edges of the passing chips. Mapping the dominant wear mechanisms showed the increasing dominance of dissolution wear relative to adhesion, with increasing grain size -- this is because a 13% larger sub-micron grain results in a larger surface area of cobalt exposed to chemical action. On the macro-scale, wear quantification through topology characterization elevated wear from a 1D to 3D concept. From investigation, a second order dependence of volumetric tool wear (VTW) and VTW rate with the material removal rate (MRR) emerged, suggesting that MRR is a more consistent wear-controlling factor instead of the traditionally used cutting speed. A predictive model for VTW was developed which showed its exponential dependence with workpiece stock volume removed. Also, both VTW and VTW rate were found to be dependent on the accumulated cumulative wear on the tool. Further, a ratio metric of stock material removed to tool volume lost is now possible as a tool efficiency quantifier and energy-based productivity parameter, which was found to inversely depend on MRR - this led to a more comprehensive tool wear definition based on cutting tool efficiency. (Abstract shortened by UMI.)

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

PubMed

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Model-based setup assistant for progressive tools

NASA Astrophysics Data System (ADS)

Springer, Robert; Gräler, Manuel; Homberg, Werner; Henke, Christian; Trächtler, Ansgar

2018-05-01

In the field of production systems, globalization and technological progress lead to increasing requirements regarding part quality, delivery time and costs. Hence, today's production is challenged much more than a few years ago: it has to be very flexible and produce economically small batch sizes to satisfy consumer's demands and avoid unnecessary stock. Furthermore, a trend towards increasing functional integration continues to lead to an ongoing miniaturization of sheet metal components. In the industry of electric connectivity for example, the miniaturized connectors are manufactured by progressive tools, which are usually used for very large batches. These tools are installed in mechanical presses and then set up by a technician, who has to manually adjust a wide range of punch-bending operations. Disturbances like material thickness, temperatures, lubrication or tool wear complicate the setup procedure. In prospect of the increasing demand of production flexibility, this time-consuming process has to be handled more and more often. In this paper, a new approach for a model-based setup assistant is proposed as a solution, which is exemplarily applied in combination with a progressive tool. First, progressive tools, more specifically, their setup process is described and based on that, the challenges are pointed out. As a result, a systematic process to set up the machines is introduced. Following, the process is investigated with an FE-Analysis regarding the effects of the disturbances. In the next step, design of experiments is used to systematically develop a regression model of the system's behaviour. This model is integrated within an optimization in order to calculate optimal machine parameters and the following necessary adjustment of the progressive tool due to the disturbances. Finally, the assistant is tested in a production environment and the results are discussed.

Test-bench system for a borehole azimuthal acoustic reflection imaging logging tool

NASA Astrophysics Data System (ADS)

Liu, Xianping; Ju, Xiaodong; Qiao, Wenxiao; Lu, Junqiang; Men, Baiyong; Liu, Dong

2016-06-01

The borehole azimuthal acoustic reflection imaging logging tool (BAAR) is a new generation of imaging logging tool, which is able to investigate stratums in a relatively larger range of space around the borehole. The BAAR is designed based on the idea of modularization with a very complex structure, so it has become urgent for us to develop a dedicated test-bench system to debug each module of the BAAR. With the help of a test-bench system introduced in this paper, test and calibration of BAAR can be easily achieved. The test-bench system is designed based on the client/server model. The hardware system mainly consists of a host computer, an embedded controlling board, a bus interface board, a data acquisition board and a telemetry communication board. The host computer serves as the human machine interface and processes the uploaded data. The software running on the host computer is designed based on VC++. The embedded controlling board uses Advanced Reduced Instruction Set Machines 7 (ARM7) as the micro controller and communicates with the host computer via Ethernet. The software for the embedded controlling board is developed based on the operating system uClinux. The bus interface board, data acquisition board and telemetry communication board are designed based on a field programmable gate array (FPGA) and provide test interfaces for the logging tool. To examine the feasibility of the test-bench system, it was set up to perform a test on BAAR. By analyzing the test results, an unqualified channel of the electronic receiving cabin was discovered. It is suggested that the test-bench system can be used to quickly determine the working condition of sub modules of BAAR and it is of great significance in improving production efficiency and accelerating industrial production of the logging tool.

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

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.

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.

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.

Tear fluid proteomics multimarkers for diabetic retinopathy screening

PubMed Central

2013-01-01

Background The aim of the project was to develop a novel method for diabetic retinopathy screening based on the examination of tear fluid biomarker changes. In order to evaluate the usability of protein biomarkers for pre-screening purposes several different approaches were used, including machine learning algorithms. Methods All persons involved in the study had diabetes. Diabetic retinopathy (DR) was diagnosed by capturing 7-field fundus images, evaluated by two independent ophthalmologists. 165 eyes were examined (from 119 patients), 55 were diagnosed healthy and 110 images showed signs of DR. Tear samples were taken from all eyes and state-of-the-art nano-HPLC coupled ESI-MS/MS mass spectrometry protein identification was performed on all samples. Applicability of protein biomarkers was evaluated by six different optimally parameterized machine learning algorithms: Support Vector Machine, Recursive Partitioning, Random Forest, Naive Bayes, Logistic Regression, K-Nearest Neighbor. Results Out of the six investigated machine learning algorithms the result of Recursive Partitioning proved to be the most accurate. The performance of the system realizing the above algorithm reached 74% sensitivity and 48% specificity. Conclusions Protein biomarkers selected and classified with machine learning algorithms alone are at present not recommended for screening purposes because of low specificity and sensitivity values. This tool can be potentially used to improve the results of image processing methods as a complementary tool in automatic or semiautomatic systems. PMID:23919537

An experimental investigation on orthogonal cutting of hybrid CFRP/Ti stacks

NASA Astrophysics Data System (ADS)

Xu, Jinyang; El Mansori, Mohamed

2016-10-01

Hybrid CFRP/Ti stack has been widely used in the modern aerospace industry owing to its superior mechanical/physical properties and excellent structural functions. Several applications require mechanical machining of these hybrid composite stacks in order to achieve dimensional accuracy and assembly performance. However, machining of such composite-to-metal alliance is usually an extremely challenging task in the manufacturing sectors due to the disparate natures of each stacked constituent and their respective poor machinability. Special issues may arise from the high force/heat generation, severe subsurface damage and rapid tool wear. To study the fundamental mechanisms controlling the bi-material machining, this paper presented an experimental study on orthogonal cutting of hybrid CFRP/Ti stack by using superior polycrystalline diamond (PCD) tipped tools. The utilized cutting parameters for hybrid CFRP/Ti machining were rigorously adopted through a compromise selection due to the disparate machinability behaviors of the CFRP laminate and Ti alloy. The key cutting responses in terms of cutting force generation, machined surface quality and tool wear mechanism were precisely addressed. The experimental results highlighted the involved five stages of CFRP/Ti cutting and the predominant crater wear and edge fracture failure governing the PCD cutting process.

Advanced composites: Fabrication processes for selected resin matrix materials

NASA Technical Reports Server (NTRS)

Welhart, E. K.

1976-01-01

This design note is based on present state of the art for epoxy and polyimide matrix composite fabrication technology. Boron/epoxy and polyimide and graphite/epoxy and polyimide structural parts can be successfully fabricated. Fabrication cycles for polyimide matrix composites have been shortened to near epoxy cycle times. Nondestructive testing has proven useful in detecting defects and anomalies in composite structure elements. Fabrication methods and tooling materials are discussed along with the advantages and disadvantages of different tooling materials. Types of honeycomb core, material costs and fabrication methods are shown in table form for comparison. Fabrication limits based on tooling size, pressure capabilities and various machining operations are also discussed.

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.

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.

FPGA-based fused smart-sensor for tool-wear area quantitative estimation in CNC machine inserts.

PubMed

Trejo-Hernandez, Miguel; Osornio-Rios, Roque Alfredo; de Jesus Romero-Troncoso, Rene; Rodriguez-Donate, Carlos; Dominguez-Gonzalez, Aurelio; Herrera-Ruiz, Gilberto

2010-01-01

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used.

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.

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

Curry, Bennett

The Arizona Commerce Authority (ACA) conducted an Innovation in Advanced Manufacturing Grant Competition to support and grow southern and central Arizona’s Aerospace and Defense (A&D) industry and its supply chain. The problem statement for this grant challenge was that many A&D machining processes utilize older generation CNC machine tool technologies that can result an inefficient use of resources – energy, time and materials – compared to the latest state-of-the-art CNC machines. Competitive awards funded projects to develop innovative new tools and technologies that reduce energy consumption for older generation machine tools and foster working relationships between industry small to medium-sizedmore » manufacturing enterprises and third-party solution providers. During the 42-month term of this grant, 12 competitive awards were made. Final reports have been included with this submission.« less

GREAT: a web portal for Genome Regulatory Architecture Tools

PubMed Central

Bouyioukos, Costas; Bucchini, François; Elati, Mohamed; Képès, François

2016-01-01

GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading. PMID:27151196

Chip morphology as a performance predictor during high speed end milling of soda lime glass

NASA Astrophysics Data System (ADS)

Bagum, M. N.; Konneh, M.; Abdullah, K. A.; Ali, M. Y.

2018-01-01

Soda lime glass has application in DNA arrays and lab on chip manufacturing. Although investigation revealed that machining of such brittle material is possible using ductile mode under controlled cutting parameters and tool geometry, it remains a challenging task. Furthermore, ability of ductile machining is usually assed through machined surface texture examination. Soda lime glass is a strain rate and temperature sensitive material. Hence, influence on attainment of ductile surface due to adiabatic heat generated during high speed end milling using uncoated tungsten carbide tool is investigated in this research. Experimental runs were designed using central composite design (CCD), taking spindle speed, feed rate and depth of cut as input variable and tool-chip contact point temperature (Ttc) and the surface roughness (Rt) as responses. Along with machined surface texture, Rt and chip morphology was examined to assess machinability of soda lime glass. The relation between Ttc and chip morphology was examined. Investigation showed that around glass transition temperature (Tg) ductile chip produced and subsequently clean and ductile final machined surface produced.

Research on intelligent monitoring technology of machining process

NASA Astrophysics Data System (ADS)

Wang, Taiyong; Meng, Changhong; Zhao, Guoli

1995-08-01

Based upon research on sound and vibration characteristics of tool condition, we explore the multigrade monitoring system which takes single-chip microcomputers as the core hardware. By using the specially designed pickup true signal devices, we can more effectively do the intelligent multigrade monitoring and forecasting, and furthermore, we can build the tool condition models adaptively. This is the key problem in FMS, CIMS, and even the IMS.

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…

Material removal characteristics of orthogonal velocity polishing tool for efficient fabrication of CVD SiC mirror surfaces

NASA Astrophysics Data System (ADS)

Seo, Hyunju; Han, Jeong-Yeol; Kim, Sug-Whan; Seong, Sehyun; Yoon, Siyoung; Lee, Kyungmook; Lee, Haengbok

2015-09-01

Today, CVD SiC mirrors are readily available in the market. However, it is well known to the community that the key surface fabrication processes and, in particular, the material removal characteristics of the CVD SiC mirror surface varies sensitively depending on the shop floor polishing and figuring variables. We investigated the material removal characteristics of CVD SiC mirror surfaces using a new and patented polishing tool called orthogonal velocity tool (OVT) that employs two orthogonal velocity fields generated simultaneously during polishing and figuring machine runs. We built an in-house OVT machine and its operating principle allows for generation of pseudo Gaussian shapes of material removal from the target surface. The shapes are very similar to the tool influence functions (TIFs) of other polishing machine such as IRP series polishing machines from Zeeko. Using two CVD SiC mirrors of 150 mm in diameter and flat surface, we ran trial material removal experiments over the machine run parameter ranges from 12.901 to 25.867 psi in pressure, 0.086 m/sec to 0.147 m/sec in tool linear velocity, and 5 to 15 sec in dwell time. An in-house developed data analysis program was used to obtain a number of Gaussian shaped TIFs and the resulting material removal coefficient varies from 3.35 to 9.46 um/psi hour m/sec with the mean value to 5.90 ± 1.26(standard deviation). We report the technical details of the new OVT machine, of the data analysis program, of the experiments and the results together with the implications to the future development of the OVT machine and process for large CVD SiC mirror surfaces.

Development of system decision support tools for behavioral trends monitoring of machinery maintenance in a competitive environment

NASA Astrophysics Data System (ADS)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani

2017-06-01

The article is centred on software system development for manufacturing company that produces polyethylene bags using mostly conventional machines in a competitive world where each business enterprise desires to stand tall. This is meant to assist in gaining market shares, taking maintenance and production decisions by the dynamism and flexibilities embedded in the package as customers' demand varies under the duress of meeting the set goals. The production and machine condition monitoring software (PMCMS) is programmed in C# and designed in such a way to support hardware integration, real-time machine conditions monitoring, which is based on condition maintenance approach, maintenance decision suggestions and suitable production strategies as the demand for products keeps changing in a highly competitive environment. PMCMS works with an embedded device which feeds it with data from the various machines being monitored at the workstation, and the data are read at the base station through transmission via a wireless transceiver and stored in a database. A case study was used in the implementation of the developed system, and the results show that it can monitor the machine's health condition effectively by displaying machines' health status, gives repair suggestions to probable faults, decides strategy for both production methods and maintenance, and, thus, can enhance maintenance performance obviously.

Prediction of turning stability using receptance coupling

NASA Astrophysics Data System (ADS)

Jasiewicz, Marcin; Powałka, Bartosz

2018-01-01

This paper presents an issue of machining stability prediction of dynamic "lathe - workpiece" system evaluated using receptance coupling method. Dynamic properties of the lathe components (the spindle and the tailstock) are assumed to be constant and can be determined experimentally based on the results of the impact test. Hence, the variable of the system "machine tool - holder - workpiece" is the machined part, which can be easily modelled analytically. The method of receptance coupling enables a synthesis of experimental (spindle, tailstock) and analytical (machined part) models, so impact testing of the entire system becomes unnecessary. The paper presents methodology of analytical and experimental models synthesis, evaluation of the stability lobes and experimental validation procedure involving both the determination of the dynamic properties of the system and cutting tests. In the summary the experimental verification results would be presented and discussed.

Dependency between removal characteristics and defined measurement categories of pellets

NASA Astrophysics Data System (ADS)

Vogt, C.; Rohrbacher, M.; Rascher, R.; Sinzinger, S.

2015-09-01

Optical surfaces are usually machined by grinding and polishing. To achieve short polishing times it is necessary to grind with best possible form accuracy and with low sub surface damages. This is possible by using very fine grained grinding tools for the finishing process. These however often show time dependent properties regarding cutting ability in conjunction with tool wear. Fine grinding tools in the optics are often pellet-tools. For a successful grinding process the tools must show a constant self-sharpening performance. A constant, at least predictable wear and cutting behavior is crucial for a deterministic machining. This work describes a method to determine the characteristics of pellet grinding tools by tests conducted with a single pellet. We investigate the determination of the effective material removal rate and the derivation of the G-ratio. Especially the change from the newly dressed via the quasi-stationary to the worn status of the tool is described. By recording the achieved roughness with the single pellet it is possible to derive the roughness expect from a series pellet tool made of pellets with the same specification. From the results of these tests the usability of a pellet grinding tool for a specific grinding task can be determined without testing a comparably expensive serial tool. The results are verified by a production test with a serial tool under series conditions. The collected data can be stored and used in an appropriate data base for tool characteristics and be combined with useful applications.

Transformer and Meter Tester

NASA Technical Reports Server (NTRS)

Stoms, R. M.

1984-01-01

Numerically-controlled 5-axis machine tool uses transformer and meter to determine and indicate whether tool is in home position, but lacks built-in test mode to check them. Tester makes possible test, and repair of components at machine rather then replace them when operation seems suspect.

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;…

Formation enthalpies for transition metal alloys using machine learning

NASA Astrophysics Data System (ADS)

Ubaru, Shashanka; Miedlar, Agnieszka; Saad, Yousef; Chelikowsky, James R.

2017-06-01

The enthalpy of formation is an important thermodynamic property. Developing fast and accurate methods for its prediction is of practical interest in a variety of applications. Material informatics techniques based on machine learning have recently been introduced in the literature as an inexpensive means of exploiting materials data, and can be used to examine a variety of thermodynamics properties. We investigate the use of such machine learning tools for predicting the formation enthalpies of binary intermetallic compounds that contain at least one transition metal. We consider certain easily available properties of the constituting elements complemented by some basic properties of the compounds, to predict the formation enthalpies. We show how choosing these properties (input features) based on a literature study (using prior physics knowledge) seems to outperform machine learning based feature selection methods such as sensitivity analysis and LASSO (least absolute shrinkage and selection operator) based methods. A nonlinear kernel based support vector regression method is employed to perform the predictions. The predictive ability of our model is illustrated via several experiments on a dataset containing 648 binary alloys. We train and validate the model using the formation enthalpies calculated using a model by Miedema, which is a popular semiempirical model used for the prediction of formation enthalpies of metal alloys.