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.

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.

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.

To select the best tool for generating 3D maintenance data and to set the detailed process for obtaining the 3D maintenance data

NASA Astrophysics Data System (ADS)

Prashanth, B. N.; Roy, Kingshuk

2017-07-01

Three Dimensional (3D) maintenance data provides a link between design and technical documentation creating interactive 3D graphical training and maintenance material. It becomes difficult for an operator to always go through huge paper manuals or come running to the computer for doing maintenance of a machine which makes the maintenance work fatigue. Above being the case, a 3D animation makes maintenance work very simple since, there is no language barrier. The research deals with the generation of 3D maintenance data of any given machine. The best tool for obtaining the 3D maintenance is selected and the tool is analyzed. Using the same tool, a detailed process for extracting the 3D maintenance data for any machine is set. This project aims at selecting the best tool for obtaining 3D maintenance data and to select the detailed process for obtaining 3D maintenance data. 3D maintenance reduces use of big volumes of manuals which creates human errors and makes the work of an operator fatiguing. Hence 3-D maintenance would help in training and maintenance and would increase productivity. 3Dvia when compared with Cortona 3D and Deep Exploration proves to be better than them. 3Dvia is good in data translation and it has the best renderings compared to the other two 3D maintenance software. 3Dvia is very user friendly and it has various options for creating 3D animations. Its Interactive Electronic Technical Publication (IETP) integration is also better than the other two software. Hence 3Dvia proves to be the best software for obtaining 3D maintenance data of any machine.

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

PubMed

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

2007-01-01

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

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.

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.

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

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.

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

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.

An experimental study of cutting performances in machining of nimonic super alloy GH2312

NASA Astrophysics Data System (ADS)

Du, Jinfu; Wang, Xi; Xu, Min; Mao, Jin; Zhao, Xinglong

2018-05-01

Nimonic super alloy are extensively used in the aerospace industry because of its unique properties. As they are quite costly and difficult to machine, the machining tool is easy to get worn. To solve the problem, an experiment was carried out on a numerical control slitting automatic lathe to analysis the tool wearing conditions and parts' surface quality of nimonic super alloy GH2132 under different cutters. The selection of suitable cutter, reasonable cutting data and cutting speed is obtained and some conclusions are made. The excellent coating tool, compared with other hard alloy cutters, along with suitable cutting data will greatly improve the production efficiency and product quality, it can completely meet the process of nimonic super alloy GH2312.

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.

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.

Machining of Fibre Reinforced Plastic Composite Materials.

PubMed

Caggiano, Alessandra

2018-03-18

Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented.

Machining of Fibre Reinforced Plastic Composite Materials

PubMed Central

2018-01-01

Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented. PMID:29562635

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.

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.

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.

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.

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.

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.

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

DOEpatents

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

1987-12-07

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

Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients.

PubMed

Park, Eunjeong; Chang, Hyuk-Jae; Nam, Hyo Suk

2017-04-18

The pronator drift test (PDT), a neurological examination, is widely used in clinics to measure motor weakness of stroke patients. The aim of this study was to develop a PDT tool with machine learning classifiers to detect stroke symptoms based on quantification of proximal arm weakness using inertial sensors and signal processing. We extracted features of drift and pronation from accelerometer signals of wearable devices on the inner wrists of 16 stroke patients and 10 healthy controls. Signal processing and feature selection approach were applied to discriminate PDT features used to classify stroke patients. A series of machine learning techniques, namely support vector machine (SVM), radial basis function network (RBFN), and random forest (RF), were implemented to discriminate stroke patients from controls with leave-one-out cross-validation. Signal processing by the PDT tool extracted a total of 12 PDT features from sensors. Feature selection abstracted the major attributes from the 12 PDT features to elucidate the dominant characteristics of proximal weakness of stroke patients using machine learning classification. Our proposed PDT classifiers had an area under the receiver operating characteristic curve (AUC) of .806 (SVM), .769 (RBFN), and .900 (RF) without feature selection, and feature selection improves the AUCs to .913 (SVM), .956 (RBFN), and .975 (RF), representing an average performance enhancement of 15.3%. Sensors and machine learning methods can reliably detect stroke signs and quantify proximal arm weakness. Our proposed solution will facilitate pervasive monitoring of stroke patients. ©Eunjeong Park, Hyuk-Jae Chang, Hyo Suk Nam. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.04.2017.

Error compensation for thermally induced errors on a machine tool

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

Krulewich, D.A.

1996-11-08

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

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.

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.

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.

Investigation of the influence of coolant-lubricant modification on selected effects of pull broaching

NASA Astrophysics Data System (ADS)

Adamczuk, Krzysztof; Legutko, Stanisław; Laber, Alicja; Serwa, Wojciech

2017-10-01

The paper presents the results of testing the wear of the tool (pull broach) and a gear wheel splineway surface roughness after the friction node of pull broach/gear wheel (CuSn12Ni2) had been lubricated with metal machining oil and the same oil modified with chemically active exploitation additive. To designate the influence of modifying metal machining oil by the exploitation additive on the lubricating properties, anti-wear and antiseizure indicators have been appointed. Exploitation tests have proved purposefulness of modifying metal machining oil. Modification of the lubricant has contributed to reduction of the wear of the tools - pull broaches and to reduction of roughness of the splineway surfaces.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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.

Manufacturing engineering: Principles for optimization

NASA Astrophysics Data System (ADS)

Koenig, Daniel T.

Various subjects in the area of manufacturing engineering are addressed. The topics considered include: manufacturing engineering organization concepts and management techniques, factory capacity and loading techniques, capital equipment programs, machine tool and equipment selection and implementation, producibility engineering, methods, planning and work management, and process control engineering in job shops. Also discussed are: maintenance engineering, numerical control of machine tools, fundamentals of computer-aided design/computer-aided manufacture, computer-aided process planning and data collection, group technology basis for plant layout, environmental control and safety, and the Integrated Productivity Improvement Program.

Application of Taguchi-grey method to optimize drilling of EMS 45 steel using minimum quantity lubrication (MQL) with multiple performance characteristics

NASA Astrophysics Data System (ADS)

Soepangkat, Bobby O. P.; Suhardjono, Pramujati, Bambang

2017-06-01

Machining under minimum quantity lubrication (MQL) has drawn the attention of researchers as an alternative to the traditionally used wet and dry machining conditions with the purpose to minimize the cooling and lubricating cost, as well as to reduce cutting zone temperature, tool wear, and hole surface roughness. Drilling is one of the important operations to assemble machine components. The objective of this study was to optimize drilling parameters such as cutting feed and cutting speed, drill type and drill point angle on the thrust force, torque, hole surface roughness and tool flank wear in drilling EMS 45 tool steel using MQL. In this study, experiments were carried out as per Taguchi design of experiments while an L18 orthogonal array was used to study the influence of various combinations of drilling parameters and tool geometries on the thrust force, torque, hole surface roughness and tool flank wear. The optimum drilling parameters was determined by using grey relational grade obtained from grey relational analysis for multiple-performance characteristics. The drilling experiments were carried out by using twist drill and CNC machining center. This work is useful for optimum values selection of various drilling parameters and tool geometries that would not only minimize the thrust force and torque, but also reduce hole surface roughness and tool flank wear.

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

High-Speed Edge Trimming of CFRP and Online Monitoring of Performance of Router Tools Using Acoustic Emission

PubMed Central

Prakash, Rangasamy; Krishnaraj, Vijayan; Zitoune, Redouane; Sheikh-Ahmad, Jamal

2016-01-01

Carbon fiber reinforced polymers (CFRPs) have found wide-ranging applications in numerous industrial fields such as aerospace, automotive, and shipping industries due to their excellent mechanical properties that lead to enhanced functional performance. In this paper, an experimental study on edge trimming of CFRP was done with various cutting conditions and different geometry of tools such as helical-, fluted-, and burr-type tools. The investigation involves the measurement of cutting forces for the different machining conditions and its effect on the surface quality of the trimmed edges. The modern cutting tools (router tools or burr tools) selected for machining CFRPs, have complex geometries in cutting edges and surfaces, and therefore a traditional method of direct tool wear evaluation is not applicable. An acoustic emission (AE) sensing was employed for on-line monitoring of the performance of router tools to determine the relationship between AE signal and length of machining for different kinds of geometry of tools. The investigation showed that the router tool with a flat cutting edge has better performance by generating lower cutting force and better surface finish with no delamination on trimmed edges. The mathematical modeling for the prediction of cutting forces was also done using Artificial Neural Network and Regression Analysis. PMID:28773919

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

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

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

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.

Effect of magnetic polarity on surface roughness during magnetic field assisted EDM of tool steel

NASA Astrophysics Data System (ADS)

Efendee, A. M.; Saifuldin, M.; Gebremariam, MA; Azhari, A.

2018-04-01

Electrical discharge machining (EDM) is one of the non-traditional machining techniques where the process offers wide range of parameters manipulation and machining applications. However, surface roughness, material removal rate, electrode wear and operation costs were among the topmost issue within this technique. Alteration of magnetic device around machining area offers exciting output to be investigated and the effects of magnetic polarity on EDM remain unacquainted. The aim of this research is to investigate the effect of magnetic polarity on surface roughness during magnetic field assisted electrical discharge machining (MFAEDM) on tool steel material (AISI 420 mod.) using graphite electrode. A Magnet with a force of 18 Tesla was applied to the EDM process at selected parameters. The sparks under magnetic field assisted EDM produced better surface finish than the normal conventional EDM process. At the presence of high magnetic field, the spark produced was squeezed and discharge craters generated on the machined surface was tiny and shallow. Correct magnetic polarity combination of MFAEDM process is highly useful to attain a high efficiency machining and improved quality of surface finish to meet the demand of modern industrial applications.

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.

Selected Articles on Machine Industry in Communist China in 1959

DTIC Science & Technology

1960-06-24

the Chinese -language periodical ■| Chi-hsieh Kung-yeh Chou-pao (Machine Industry weekly), • Peiping. Date of issue, page and author, if any are... Chinese Communist Party, had a rapid development. During the three- - year rehabilitation period, economic .rehabilitation work was vigorously...balances,, which.were designed by Chinese workers, are an important tool for use in complex scientific and technical studies. ■- ^ On radio

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Technology of high-speed combined machining with brush electrode

NASA Astrophysics Data System (ADS)

Kirillov, O. N.; Smolentsev, V. P.; Yukhnevich, S. S.

2018-03-01

The new method was proposed for high-precision dimensional machining with a brush electrode when the true position of bundles of metal wire is adjusted by means of creating controlled centrifugal forces appeared due to the increased frequency of rotation of a tool. There are the ultimate values of circumferential velocity at which the bundles are pressed against a machined area of a workpiece in a stable manner despite the profile of the machined surface and variable stock of the workpiece. The special aspects of design of processing procedures for finishing standard parts, including components of products with low rigidity, are disclosed. The methodology of calculation and selection of processing modes which allow one to produce high-precision details and to provide corresponding surface roughness required to perform finishing operations (including the preparation of a surface for metal deposition) is presented. The production experience concerned with the use of high-speed combined machining with an unshaped tool electrode in knowledge-intensive branches of the machine-building industry for different types of production is analyzed. It is shown that the implementation of high-speed dimensional machining with an unshaped brush electrode allows one to expand the field of use of the considered process due to the application of a multipurpose tool in the form of a metal brush, as well as to obtain stable results of finishing and to provide the opportunities for long-term operation of the equipment without its changeover and readjustment.

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.

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.

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.

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.

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.

Developing Instructional Applications at the Secondary Level. The Computer as a Tool.

ERIC Educational Resources Information Center

McManus, Jack; And Others

Case studies are presented for seven Los Angeles area (California) high schools that worked with Pepperdine University in the IBM/ETS (International Business Machines/Educational Testing Service) Model Schools program, a project which provided training for selected secondary school teachers in the use of personal computers and selected software as…

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…

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.

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.

The dynamic analysis of drum roll lathe for machining of rollers

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

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.

Selection of Additive Manufacturing (AM) Equipment

DTIC Science & Technology

2017-04-01

in the design , test, and fabrication of the systems within the AMRDEC portfolio. 14. SUBJECT TERMS Additive Manufacturing (AM), Fused Deposition...tools in the design and development of AMRDEC products .   Figure 1. Stratasys Objet Connex3 [1] While these machines and technologies have...TECHNICAL REPORT RDMR-WD-16-87 SELECTION OF ADDITIVE MANUFACTURING (AM) EQUIPMENT Lance E. Hall Weapons Development

[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.

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

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.

Towards a generalized energy prediction model for machine tools

PubMed Central

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

2017-01-01

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

Towards a generalized energy prediction model for machine tools.

PubMed

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

2017-04-01

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

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…

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

PubMed

Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro

2016-12-15

MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.

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.

Running accuracy analysis of a 3-RRR parallel kinematic machine considering the deformations of the links

NASA Astrophysics Data System (ADS)

Wang, Liping; Jiang, Yao; Li, Tiemin

2014-09-01

Parallel kinematic machines have drawn considerable attention and have been widely used in some special fields. However, high precision is still one of the challenges when they are used for advanced machine tools. One of the main reasons is that the kinematic chains of parallel kinematic machines are composed of elongated links that can easily suffer deformations, especially at high speeds and under heavy loads. A 3-RRR parallel kinematic machine is taken as a study object for investigating its accuracy with the consideration of the deformations of its links during the motion process. Based on the dynamic model constructed by the Newton-Euler method, all the inertia loads and constraint forces of the links are computed and their deformations are derived. Then the kinematic errors of the machine are derived with the consideration of the deformations of the links. Through further derivation, the accuracy of the machine is given in a simple explicit expression, which will be helpful to increase the calculating speed. The accuracy of this machine when following a selected circle path is simulated. The influences of magnitude of the maximum acceleration and external loads on the running accuracy of the machine are investigated. The results show that the external loads will deteriorate the accuracy of the machine tremendously when their direction coincides with the direction of the worst stiffness of the machine. The proposed method provides a solution for predicting the running accuracy of the parallel kinematic machines and can also be used in their design optimization as well as selection of suitable running parameters.

Research on ARM Numerical Control System

NASA Astrophysics Data System (ADS)

Wei, Xu; JiHong, Chen

Computerized Numerical Control (CNC) machine tools is the foundation of modern manufacturing systems, whose advanced digital technology is the key to solve the problem of sustainable development of machine tool manufacturing industry. The paper is to design CNC system embedded on ARM and indicates the hardware design and the software systems supported. On the hardware side: the driving chip of the motor control unit, as the core of components, is MCX314AL of DSP motion control which is developed by NOVA Electronics Co., Ltd. of Japan. It make convenient to control machine because of its excellent performance, simple interface, easy programming. On the Software side, the uC/OS-2 is selected as the embedded operating system of the open source, which makes a detailed breakdown of the modules of the CNC system. Those priorities are designed according to their actual requirements. The ways of communication between the module and the interrupt response are so different that it guarantees real-time property and reliability of the numerical control system. Therefore, it not only meets the requirements of the current social precision machining, but has good man-machine interface and network support to facilitate a variety of craftsmen use.

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

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

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.

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.

Nanocomposites for Machining Tools

PubMed Central

Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

2017-01-01

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

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.

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.

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.

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.

Why don’t you use Evolutionary Algorithms in Big Data?

NASA Astrophysics Data System (ADS)

Stanovov, Vladimir; Brester, Christina; Kolehmainen, Mikko; Semenkina, Olga

2017-02-01

In this paper we raise the question of using evolutionary algorithms in the area of Big Data processing. We show that evolutionary algorithms provide evident advantages due to their high scalability and flexibility, their ability to solve global optimization problems and optimize several criteria at the same time for feature selection, instance selection and other data reduction problems. In particular, we consider the usage of evolutionary algorithms with all kinds of machine learning tools, such as neural networks and fuzzy systems. All our examples prove that Evolutionary Machine Learning is becoming more and more important in data analysis and we expect to see the further development of this field especially in respect to Big Data.

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)…

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

PubMed

Luo, Gang

2016-01-01

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

AMS 4.0: consensus prediction of post-translational modifications in protein sequences.

PubMed

Plewczynski, Dariusz; Basu, Subhadip; Saha, Indrajit

2012-08-01

We present here the 2011 update of the AutoMotif Service (AMS 4.0) that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The selection of experimentally confirmed modifications is acquired from the latest UniProt and Phospho.ELM databases for training. The sequence vicinity of each modified residue is represented using amino acids physico-chemical features encoded using high quality indices (HQI) obtaining by automatic clustering of known indices extracted from AAindex database. For each type of the numerical representation, the method builds the ensemble of Multi-Layer Perceptron (MLP) pattern classifiers, each optimising different objectives during the training (for example the recall, precision or area under the ROC curve (AUC)). The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs. The performance of AMS 4.0 is compared with the accuracy of previous versions, which were constructed using single machine learning methods (artificial neural networks, support vector machine). Our software improves the average AUC score of the earlier version by close to 7 % as calculated on the test datasets of all 88 PTM types. Moreover, for the selected most-difficult sequence motifs types it is able to improve the prediction performance by almost 32 %, when compared with previously used single machine learning methods. Summarising, the brainstorming consensus meta-learning methodology on the average boosts the AUC score up to around 89 %, averaged over all 88 PTM types. Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools. The source code and precompiled binaries of brainstorming tool are available at http://code.google.com/p/automotifserver/ under Apache 2.0 licensing.

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...

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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.

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

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

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

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

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

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

Investigation of roughing machining simulation by using visual basic programming in NX CAM system

NASA Astrophysics Data System (ADS)

Hafiz Mohamad, Mohamad; Nafis Osman Zahid, Muhammed

2018-03-01

This paper outlines a simulation study to investigate the characteristic of roughing machining simulation in 4th axis milling processes by utilizing visual basic programming in NX CAM systems. The selection and optimization of cutting orientation in rough milling operation is critical in 4th axis machining. The main purpose of roughing operation is to approximately shape the machined parts into finished form by removing the bulk of material from workpieces. In this paper, the simulations are executed by manipulating a set of different cutting orientation to generate estimated volume removed from the machine parts. The cutting orientation with high volume removal is denoted as an optimum value and chosen to execute a roughing operation. In order to run the simulation, customized software is developed to assist the routines. Operations build-up instructions in NX CAM interface are translated into programming codes via advanced tool available in the Visual Basic Studio. The codes is customized and equipped with decision making tools to run and control the simulations. It permits the integration with any independent program files to execute specific operations. This paper aims to discuss about the simulation program and identifies optimum cutting orientations for roughing processes. The output of this study will broaden up the simulation routines performed in NX CAM systems.

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

PubMed Central

Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki

2013-01-01

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846

AE Monitoring of Diamond Turned Rapidly Soldified Aluminium 443

NASA Astrophysics Data System (ADS)

Onwuka, G.; Abou-El-Hossein, K.; Mkoko, Z.

2017-05-01

The fast replacement of conventional aluminium with rapidly solidified aluminium alloys has become a noticeable trend in the current manufacturing industries involved in the production of optics and optical molding inserts. This is as a result of the improved performance and durability of rapidly solidified aluminium alloys when compared to conventional aluminium. Melt spinning process is vital for manufacturing rapidly solidified aluminium alloys like RSA 905, RSA 6061 and RSA 443 which are common in the industries today. RSA 443 is a newly developed alloy with few research findings and huge research potential. There is no available literature focused on monitoring the machining of RSA 443 alloys. In this research, Acoustic Emission sensing technique was applied to monitor the single point diamond turning of RSA 443 on an ultrahigh precision lathe machine. The machining process was carried out after careful selection of feed, speed and depths of cut. The monitoring process was achieved with a high sampling data acquisition system using different tools while concurrent measurement of the surface roughness and tool wear were initiated after covering a total feed distance of 13km. An increasing trend of raw AE spikes and peak to peak signal were observed with an increase in the surface roughness and tool wear values. Hence, acoustic emission sensing technique proves to be an effective monitoring method for the machining of RSA 443 alloy.

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

Vocational Reintegration of Handicapped Workers with Assistive Devices

ERIC Educational Resources Information Center

Cooper, N. E.

1977-01-01

Two approaches to vocational reintegration of handicapped workers are described: (1) adapting the disabled to the working environment through treatment, therapy, counseling, selective placement, and prostheses, and (2) adapting the working environment to particular handicaps, with the assistive device fitted to the machine or tool rather than to…

Applied Physics Modules Selected for Manufacturing and Metal Technologies.

ERIC Educational Resources Information Center

Waring, Gene

Designed for individualized use in an applied physics course in postsecondary vocational-technical education, this series of eighteen learning modules is equivalent to the content of two quarters of a five-credit hour class in manufacturing engineering technology, machine tool and design technology, welding technology, and industrial plastics…

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

NASA Astrophysics Data System (ADS)

Dasgupta, S.; Mukherjee, S.

2016-09-01

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

Highly Productive Tools For Turning And Milling

NASA Astrophysics Data System (ADS)

Vasilko, Karol

2015-12-01

Beside cutting speed, shift is another important parameter of machining. Its considerable influence is shown mainly in the workpiece machined surface microgeometry. In practice, mainly its combination with the radius of cutting tool tip rounding is used. Options to further increase machining productivity and machined surface quality are hidden in this approach. The paper presents variations of the design of productive cutting tools for lathe work and milling on the base of the use of the laws of the relationship among the highest reached uneveness of machined surface, tool tip radius and shift.

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.

Influence of Wire Electrical Discharge Machining (WEDM) process parameters on surface roughness

NASA Astrophysics Data System (ADS)

Yeakub Ali, Mohammad; Banu, Asfana; Abu Bakar, Mazilah

2018-01-01

In obtaining the best quality of engineering components, the quality of machined parts surface plays an important role. It improves the fatigue strength, wear resistance, and corrosion of workpiece. This paper investigates the effects of wire electrical discharge machining (WEDM) process parameters on surface roughness of stainless steel using distilled water as dielectric fluid and brass wire as tool electrode. The parameters selected are voltage open, wire speed, wire tension, voltage gap, and off time. Empirical model was developed for the estimation of surface roughness. The analysis revealed that off time has a major influence on surface roughness. The optimum machining parameters for minimum surface roughness were found to be at a 10 V open voltage, 2.84 μs off time, 12 m/min wire speed, 6.3 N wire tension, and 54.91 V voltage gap.

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.

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PubMed

Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

2015-01-01

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

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.

Modeling and Analysis of CNC Milling Process Parameters on Al3030 based Composite

NASA Astrophysics Data System (ADS)

Gupta, Anand; Soni, P. K.; Krishna, C. M.

2018-04-01

The machining of Al3030 based composites on Computer Numerical Control (CNC) high speed milling machine have assumed importance because of their wide application in aerospace industries, marine industries and automotive industries etc. Industries mainly focus on surface irregularities; material removal rate (MRR) and tool wear rate (TWR) which usually depends on input process parameters namely cutting speed, feed in mm/min, depth of cut and step over ratio. Many researchers have carried out researches in this area but very few have taken step over ratio or radial depth of cut also as one of the input variables. In this research work, the study of characteristics of Al3030 is carried out at high speed CNC milling machine over the speed range of 3000 to 5000 r.p.m. Step over ratio, depth of cut and feed rate are other input variables taken into consideration in this research work. A total nine experiments are conducted according to Taguchi L9 orthogonal array. The machining is carried out on high speed CNC milling machine using flat end mill of diameter 10mm. Flatness, MRR and TWR are taken as output parameters. Flatness has been measured using portable Coordinate Measuring Machine (CMM). Linear regression models have been developed using Minitab 18 software and result are validated by conducting selected additional set of experiments. Selection of input process parameters in order to get best machining outputs is the key contributions of this research work.

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.

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.

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

Analysis of acoustic emission signals and monitoring of machining processes

PubMed

Govekar; Gradisek; Grabec

2000-03-01

Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.

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

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

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

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.

Vibration Damping Analysis of Lightweight Structures in Machine Tools

PubMed Central

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

2017-01-01

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

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.

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.

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.

Classification of the fragrant styles and evaluation of the aromatic quality of flue-cured tobacco leaves by machine-learning methods.

PubMed

Gu, Li; Xue, Lichun; Song, Qi; Wang, Fengji; He, Huaqin; Zhang, Zhongyi

2016-12-01

During commercial transactions, the quality of flue-cured tobacco leaves must be characterized efficiently, and the evaluation system should be easily transferable across different traders. However, there are over 3000 chemical compounds in flue-cured tobacco leaves; thus, it is impossible to evaluate the quality of flue-cured tobacco leaves using all the chemical compounds. In this paper, we used Support Vector Machine (SVM) algorithm together with 22 chemical compounds selected by ReliefF-Particle Swarm Optimization (R-PSO) to classify the fragrant style of flue-cured tobacco leaves, where the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) were 90.95% and 0.80, respectively. SVM algorithm combined with 19 chemical compounds selected by R-PSO achieved the best assessment performance of the aromatic quality of tobacco leaves, where the PCC and MSE were 0.594 and 0.263, respectively. Finally, we constructed two online tools to classify the fragrant style and evaluate the aromatic quality of flue-cured tobacco leaf samples. These tools can be accessed at http://bioinformatics.fafu.edu.cn/tobacco .

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.

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.

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.

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…

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

Low Cost Injection Mold Creation via Hybrid Additive and Conventional Manufacturing

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

Dehoff, Ryan R.; Watkins, Thomas R.; List, III, Frederick Alyious

2015-12-01

The purpose of the proposed project between Cummins and ORNL is to significantly reduce the cost of the tooling (machining and materials) required to create injection molds to make plastic components. Presently, the high cost of this tooling forces the design decision to make cast aluminum parts because Cummins typical production volumes are too low to allow injection molded plastic parts to be cost effective with the amortized cost of the injection molding tooling. In addition to reducing the weight of components, polymer injection molding allows the opportunity for the alternative cooling methods, via nitrogen gas. Nitrogen gas cooling offersmore » an environmentally and economically attractive cooling option, if the mold can be manufactured economically. In this project, a current injection molding design was optimized for cooling using nitrogen gas. The various components of the injection mold tooling were fabricated using the Renishaw powder bed laser additive manufacturing technology. Subsequent machining was performed on the as deposited components to form a working assembly. The injection mold is scheduled to be tested in a projection setting at a commercial vendor selected by Cummins.« less

Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features.

PubMed

Shim, Miseon; Hwang, Han-Jeong; Kim, Do-Won; Lee, Seung-Hwan; Im, Chang-Hwan

2016-10-01

Recently, an increasing number of researchers have endeavored to develop practical tools for diagnosing patients with schizophrenia using machine learning techniques applied to EEG biomarkers. Although a number of studies showed that source-level EEG features can potentially be applied to the differential diagnosis of schizophrenia, most studies have used only sensor-level EEG features such as ERP peak amplitude and power spectrum for machine learning-based diagnosis of schizophrenia. In this study, we used both sensor-level and source-level features extracted from EEG signals recorded during an auditory oddball task for the classification of patients with schizophrenia and healthy controls. EEG signals were recorded from 34 patients with schizophrenia and 34 healthy controls while each subject was asked to attend to oddball tones. Our results demonstrated higher classification accuracy when source-level features were used together with sensor-level features, compared to when only sensor-level features were used. In addition, the selected sensor-level features were mostly found in the frontal area, and the selected source-level features were mostly extracted from the temporal area, which coincide well with the well-known pathological region of cognitive processing in patients with schizophrenia. Our results suggest that our approach would be a promising tool for the computer-aided diagnosis of schizophrenia. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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

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.

Fizzy: feature subset selection for metagenomics.

PubMed

Ditzler, Gregory; Morrison, J Calvin; Lan, Yemin; Rosen, Gail L

2015-11-04

Some of the current software tools for comparative metagenomics provide ecologists with the ability to investigate and explore bacterial communities using α- & β-diversity. Feature subset selection--a sub-field of machine learning--can also provide a unique insight into the differences between metagenomic or 16S phenotypes. In particular, feature subset selection methods can obtain the operational taxonomic units (OTUs), or functional features, that have a high-level of influence on the condition being studied. For example, in a previous study we have used information-theoretic feature selection to understand the differences between protein family abundances that best discriminate between age groups in the human gut microbiome. We have developed a new Python command line tool, which is compatible with the widely adopted BIOM format, for microbial ecologists that implements information-theoretic subset selection methods for biological data formats. We demonstrate the software tools capabilities on publicly available datasets. We have made the software implementation of Fizzy available to the public under the GNU GPL license. The standalone implementation can be found at http://github.com/EESI/Fizzy.

Fizzy. Feature subset selection for metagenomics

DOE PAGES

Ditzler, Gregory; Morrison, J. Calvin; Lan, Yemin; ...

2015-11-04

Background: Some of the current software tools for comparative metagenomics provide ecologists with the ability to investigate and explore bacterial communities using α– & β–diversity. Feature subset selection – a sub-field of machine learning – can also provide a unique insight into the differences between metagenomic or 16S phenotypes. In particular, feature subset selection methods can obtain the operational taxonomic units (OTUs), or functional features, that have a high-level of influence on the condition being studied. For example, in a previous study we have used information-theoretic feature selection to understand the differences between protein family abundances that best discriminate betweenmore » age groups in the human gut microbiome. Results: We have developed a new Python command line tool, which is compatible with the widely adopted BIOM format, for microbial ecologists that implements information-theoretic subset selection methods for biological data formats. We demonstrate the software tools capabilities on publicly available datasets. Conclusions: We have made the software implementation of Fizzy available to the public under the GNU GPL license. The standalone implementation can be found at http://github.com/EESI/Fizzy.« less

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.

Configuration Management and Infrastructure Monitoring Using CFEngine and Icinga for Real-time Heterogeneous Data Taking Environment

NASA Astrophysics Data System (ADS)

Poat, M. D.; Lauret, J.; Betts, W.

2015-12-01

The STAR online computing environment is an intensive ever-growing system used for real-time data collection and analysis. Composed of heterogeneous and sometimes groups of custom-tuned machines, the computing infrastructure was previously managed by manual configurations and inconsistently monitored by a combination of tools. This situation led to configuration inconsistency and an overload of repetitive tasks along with lackluster communication between personnel and machines. Globally securing this heterogeneous cyberinfrastructure was tedious at best and an agile, policy-driven system ensuring consistency, was pursued. Three configuration management tools, Chef, Puppet, and CFEngine have been compared in reliability, versatility and performance along with a comparison of infrastructure monitoring tools Nagios and Icinga. STAR has selected the CFEngine configuration management tool and the Icinga infrastructure monitoring system leading to a versatile and sustainable solution. By leveraging these two tools STAR can now swiftly upgrade and modify the environment to its needs with ease as well as promptly react to cyber-security requests. By creating a sustainable long term monitoring solution, the detection of failures was reduced from days to minutes, allowing rapid actions before the issues become dire problems, potentially causing loss of precious experimental data or uptime.

More complete gene silencing by fewer siRNAs: transparent optimized design and biophysical signature

PubMed Central

Ladunga, Istvan

2007-01-01

Highly accurate knockdown functional analyses based on RNA interference (RNAi) require the possible most complete hydrolysis of the targeted mRNA while avoiding the degradation of untargeted genes (off-target effects). This in turn requires significant improvements to target selection for two reasons. First, the average silencing activity of randomly selected siRNAs is as low as 62%. Second, applying more than five different siRNAs may lead to saturation of the RNA-induced silencing complex (RISC) and to the degradation of untargeted genes. Therefore, selecting a small number of highly active siRNAs is critical for maximizing knockdown and minimizing off-target effects. To satisfy these needs, a publicly available and transparent machine learning tool is presented that ranks all possible siRNAs for each targeted gene. Support vector machines (SVMs) with polynomial kernels and constrained optimization models select and utilize the most predictive effective combinations from 572 sequence, thermodynamic, accessibility and self-hairpin features over 2200 published siRNAs. This tool reaches an accuracy of 92.3% in cross-validation experiments. We fully present the underlying biophysical signature that involves free energy, accessibility and dinucleotide characteristics. We show that while complete silencing is possible at certain structured target sites, accessibility information improves the prediction of the 90% active siRNA target sites. Fast siRNA activity predictions can be performed on our web server at . PMID:17169992

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.

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

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.

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…

ReliefSeq: A Gene-Wise Adaptive-K Nearest-Neighbor Feature Selection Tool for Finding Gene-Gene Interactions and Main Effects in mRNA-Seq Gene Expression Data

PubMed Central

McKinney, Brett A.; White, Bill C.; Grill, Diane E.; Li, Peter W.; Kennedy, Richard B.; Poland, Gregory A.; Oberg, Ann L.

2013-01-01

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php. PMID:24339943

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

ERIC Educational Resources Information Center

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

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

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.

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…

Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits

PubMed Central

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris

2016-01-01

Phenotyping local crop cultivars is becoming more and more important, as they are an important genetic source for breeding – especially in regard to inherent root system architectures. Machine learning algorithms are promising tools to assist in the analysis of complex data sets; novel approaches are need to apply them on root phenotyping data of mature plants. A greenhouse experiment was conducted in large, sand-filled columns to differentiate 16 European Pisum sativum cultivars based on 36 manually derived root traits. Through combining random forest and support vector machine models, machine learning algorithms were successfully used for unbiased identification of most distinguishing root traits and subsequent pairwise cultivar differentiation. Up to 86% of pea cultivar pairs could be distinguished based on top five important root traits (Timp5) – Timp5 differed widely between cultivar pairs. Selecting top important root traits (Timp) provided a significant improved classification compared to using all available traits or randomly selected trait sets. The most frequent Timp of mature pea cultivars was total surface area of lateral roots originating from tap root segments at 0–5 cm depth. The high classification rate implies that culturing did not lead to a major loss of variability in root system architecture in the studied pea cultivars. Our results illustrate the potential of machine learning approaches for unbiased (root) trait selection and cultivar classification based on rather small, complex phenotypic data sets derived from pot experiments. Powerful statistical approaches are essential to make use of the increasing amount of (root) phenotyping information, integrating the complex trait sets describing crop cultivars. PMID:27999587

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

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

On-line Tool Wear Detection on DCMT070204 Carbide Tool Tip Based on Noise Cutting Audio Signal using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Prasetyo, T.; Amar, S.; Arendra, A.; Zam Zami, M. K.

2018-01-01

This study develops an on-line detection system to predict the wear of DCMT070204 tool tip during the cutting process of the workpiece. The machine used in this research is CNC ProTurn 9000 to cut ST42 steel cylinder. The audio signal has been captured using the microphone placed in the tool post and recorded in Matlab. The signal is recorded at the sampling rate of 44.1 kHz, and the sampling size of 1024. The recorded signal is 110 data derived from the audio signal while cutting using a normal chisel and a worn chisel. And then perform signal feature extraction in the frequency domain using Fast Fourier Transform. Feature selection is done based on correlation analysis. And tool wear classification was performed using artificial neural networks with 33 input features selected. This artificial neural network is trained with back propagation method. Classification performance testing yields an accuracy of 74%.

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.

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

PubMed

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

2016-10-01

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

Constrained Optimization Problems in Cost and Managerial Accounting--Spreadsheet Tools

ERIC Educational Resources Information Center

Amlie, Thomas T.

2009-01-01

A common problem addressed in Managerial and Cost Accounting classes is that of selecting an optimal production mix given scarce resources. That is, if a firm produces a number of different products, and is faced with scarce resources (e.g., limitations on labor, materials, or machine time), what combination of products yields the greatest profit…

A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.

PubMed

Chen, Zhenyu; Li, Jianping; Wei, Liwei

2007-10-01

Recently, gene expression profiling using microarray techniques has been shown as a promising tool to improve the diagnosis and treatment of cancer. Gene expression data contain high level of noise and the overwhelming number of genes relative to the number of available samples. It brings out a great challenge for machine learning and statistic techniques. Support vector machine (SVM) has been successfully used to classify gene expression data of cancer tissue. In the medical field, it is crucial to deliver the user a transparent decision process. How to explain the computed solutions and present the extracted knowledge becomes a main obstacle for SVM. A multiple kernel support vector machine (MK-SVM) scheme, consisting of feature selection, rule extraction and prediction modeling is proposed to improve the explanation capacity of SVM. In this scheme, we show that the feature selection problem can be translated into an ordinary multiple parameters learning problem. And a shrinkage approach: 1-norm based linear programming is proposed to obtain the sparse parameters and the corresponding selected features. We propose a novel rule extraction approach using the information provided by the separating hyperplane and support vectors to improve the generalization capacity and comprehensibility of rules and reduce the computational complexity. Two public gene expression datasets: leukemia dataset and colon tumor dataset are used to demonstrate the performance of this approach. Using the small number of selected genes, MK-SVM achieves encouraging classification accuracy: more than 90% for both two datasets. Moreover, very simple rules with linguist labels are extracted. The rule sets have high diagnostic power because of their good classification performance.

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).…

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.

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.

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.

Closeout of CRADA JSA 2012S004: Chapter 5, Integrated Control System, of the document of the ESS Conceptual Design Report, publicly available at https://europeanspallationsource.se/accelerator-documents

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

Satogata, Todd

2013-04-22

The integrated control system (ICS) is responsible for the whole ESS machine and facility: accelerator, target, neutron scattering instruments and conventional facilities. This unified approach keeps the costs of development, maintenance and support relatively low. ESS has selected a standardised, field-proven controls framework, the Experimental Physics and Industrial Control System (EPICS), which was originally developed jointly by Argonne and Los Alamos National Laboratories. Complementing this selection are best practices and experience from similar facilities regarding platform standardisation, control system development and device integration and commissioning. The components of ICS include the control system core, the control boxes, the BLED databasemore » management system, and the human machine interface. The control system core is a set of systems and tools that make it possible for the control system to provide required data, information and services to engineers, operators, physicists and the facility itself. The core components are the timing system that makes possible clock synchronisation across the facility, the machine protection system (MPS) and the personnel protection system (PPS) that prevent damage to the machine and personnel, and a set of control system services. Control boxes are servers that control a collection of equipment (for example a radio frequency cavity). The integrated control system will include many control boxes that can be assigned to one supplier, such as an internal team, a collaborating institute or a commercial vendor. This approach facilitates a clear division of responsibilities and makes integration much easier. A control box is composed of a standardised hardware platform, components, development tools and services. On the top level, it interfaces with the core control system components (timing, MPS, PPS) and with the human-machine interface. At the bottom, it interfaces with the equipment and parts of the facility through a set of analog and digital signals, real-time control loops and other communication buses. The ICS central data management system is named BLED (beam line element databases). BLED is a set of databases, tools and services that is used to store, manage and access data. It holds vital control system configuration and physics-related (lattice) information about the accelerator, target and instruments. It facilitates control system configuration by bringing together direct input-output controller (IOC) con guration and real-time data from proton and neutron beam line models. BLED also simplifies development and speeds up the code-test-debug cycle. The set of tools that access BLED will be tailored to the needs of different categories of users, such as ESS staff physicists, engineers, and operators; external partner laboratories; and visiting experimental instrument users. The human-machine interface is vital to providing a high-quality experience to ICS users. It encompasses a wide array of devices and software tools, from control room screens to engineer terminal windows; from beam physics data tools to post-mortem data analysis tools. It serves users with a wide range of skills from widely varied backgrounds. The Controls Group is developing a set of user profiles to accommodate this diverse range of use-cases and users.« less

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 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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

Machine learning is a powerful but underutilized approach that can enable planetary scientists to derive meaningful results from the rapidly-growing quantity of available spectral data. For example, regression methods such as Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO), can be used to determine chemical concentrations from ChemCam and SuperCam Laser-Induced Breakdown Spectroscopy (LIBS) data [1]. Many scientists are interested in testing different spectral data processing and machine learning methods, but few have the time or expertise to write their own software to do so. We are therefore developing a free open-source library of software called the Python Spectral Analysis Tool (PySAT) along with a flexible, user-friendly graphical interface to enable scientists to process and analyze point spectral data without requiring significant programming or machine-learning expertise. A related but separately-funded effort is working to develop a graphical interface for orbital data [2]. The PySAT point-spectra tool includes common preprocessing steps (e.g. interpolation, normalization, masking, continuum removal, dimensionality reduction), plotting capabilities, and capabilities to prepare data for machine learning such as creating stratified folds for cross validation, defining training and test sets, and applying calibration transfer so that data collected on different instruments or under different conditions can be used together. The tool leverages the scikit-learn library [3] to enable users to train and compare the results from a variety of multivariate regression methods. It also includes the ability to combine multiple "sub-models" into an overall model, a method that has been shown to improve results and is currently used for ChemCam data [4]. Although development of the PySAT point-spectra tool has focused primarily on the analysis of LIBS spectra, the relevant steps and methods are applicable to any spectral data. The tool is available at https://github.com/USGS-Astrogeology/PySAT_Point_Spectra_GUI. [1] Clegg, S.M., et al. (2017) Spectrochim Acta B. 129, 64-85. [2] Gaddis, L. et al. (2017) 3rd Planetary Data Workshop, #1986. [3] http://scikit-learn.org/ [4] Anderson, R.B., et al. (2017) Spectrochim. Acta B. 129, 49-57.

The Methodology of Calculation of Cutting Forces When Machining Composite Materials

NASA Astrophysics Data System (ADS)

Rychkov, D. A.; Yanyushkin, A. S.

2016-08-01

Cutting of composite materials has specific features and is different from the processing of metals. When this characteristic intense wear of the cutting tool. An important criterion in the selection process parameters composite processing is the value of the cutting forces, which depends on many factors and is determined experimentally, it is not always appropriate. The study developed a method of determining the cutting forces when machining composite materials and the comparative evaluation of the calculated and actual values of cutting forces. The methodology for calculating cutting forces into account specific features of the cutting tool and the extent of wear, the strength properties of the processed material and cutting conditions. Experimental studies conducted with fiberglass milling cutter equipped with elements of hard metal VK3M. The discrepancy between the estimated and the actual values of the cutting force is not more than 10%.

Validation results of specifications for motion control interoperability

NASA Astrophysics Data System (ADS)

Szabo, Sandor; Proctor, Frederick M.

1997-01-01

The National Institute of Standards and Technology (NIST) is participating in the Department of Energy Technologies Enabling Agile Manufacturing (TEAM) program to establish interface standards for machine tool, robot, and coordinate measuring machine controllers. At NIST, the focus is to validate potential application programming interfaces (APIs) that make it possible to exchange machine controller components with a minimal impact on the rest of the system. This validation is taking place in the enhanced machine controller (EMC) consortium and is in cooperation with users and vendors of motion control equipment. An area of interest is motion control, including closed-loop control of individual axes and coordinated path planning. Initial tests of the motion control APIs are complete. The APIs were implemented on two commercial motion control boards that run on two different machine tools. The results for a baseline set of APIs look promising, but several issues were raised. These include resolving differing approaches in how motions are programmed and defining a standard measurement of performance for motion control. This paper starts with a summary of the process used in developing a set of specifications for motion control interoperability. Next, the EMC architecture and its classification of motion control APIs into two classes, Servo Control and Trajectory Planning, are reviewed. Selected APIs are presented to explain the basic functionality and some of the major issues involved in porting the APIs to other motion controllers. The paper concludes with a summary of the main issues and ways to continue the standards process.

The construction of support vector machine classifier using the firefly algorithm.

PubMed

Chao, Chih-Feng; Horng, Ming-Huwi

2015-01-01

The setting of parameters in the support vector machines (SVMs) is very important with regard to its accuracy and efficiency. In this paper, we employ the firefly algorithm to train all parameters of the SVM simultaneously, including the penalty parameter, smoothness parameter, and Lagrangian multiplier. The proposed method is called the firefly-based SVM (firefly-SVM). This tool is not considered the feature selection, because the SVM, together with feature selection, is not suitable for the application in a multiclass classification, especially for the one-against-all multiclass SVM. In experiments, binary and multiclass classifications are explored. In the experiments on binary classification, ten of the benchmark data sets of the University of California, Irvine (UCI), machine learning repository are used; additionally the firefly-SVM is applied to the multiclass diagnosis of ultrasonic supraspinatus images. The classification performance of firefly-SVM is also compared to the original LIBSVM method associated with the grid search method and the particle swarm optimization based SVM (PSO-SVM). The experimental results advocate the use of firefly-SVM to classify pattern classifications for maximum accuracy.

The Construction of Support Vector Machine Classifier Using the Firefly Algorithm

PubMed Central

Chao, Chih-Feng; Horng, Ming-Huwi

2015-01-01

The setting of parameters in the support vector machines (SVMs) is very important with regard to its accuracy and efficiency. In this paper, we employ the firefly algorithm to train all parameters of the SVM simultaneously, including the penalty parameter, smoothness parameter, and Lagrangian multiplier. The proposed method is called the firefly-based SVM (firefly-SVM). This tool is not considered the feature selection, because the SVM, together with feature selection, is not suitable for the application in a multiclass classification, especially for the one-against-all multiclass SVM. In experiments, binary and multiclass classifications are explored. In the experiments on binary classification, ten of the benchmark data sets of the University of California, Irvine (UCI), machine learning repository are used; additionally the firefly-SVM is applied to the multiclass diagnosis of ultrasonic supraspinatus images. The classification performance of firefly-SVM is also compared to the original LIBSVM method associated with the grid search method and the particle swarm optimization based SVM (PSO-SVM). The experimental results advocate the use of firefly-SVM to classify pattern classifications for maximum accuracy. PMID:25802511

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

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…

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.

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

Ditzler, Gregory; Morrison, J. Calvin; Lan, Yemin

Background: Some of the current software tools for comparative metagenomics provide ecologists with the ability to investigate and explore bacterial communities using α– & β–diversity. Feature subset selection – a sub-field of machine learning – can also provide a unique insight into the differences between metagenomic or 16S phenotypes. In particular, feature subset selection methods can obtain the operational taxonomic units (OTUs), or functional features, that have a high-level of influence on the condition being studied. For example, in a previous study we have used information-theoretic feature selection to understand the differences between protein family abundances that best discriminate betweenmore » age groups in the human gut microbiome. Results: We have developed a new Python command line tool, which is compatible with the widely adopted BIOM format, for microbial ecologists that implements information-theoretic subset selection methods for biological data formats. We demonstrate the software tools capabilities on publicly available datasets. Conclusions: We have made the software implementation of Fizzy available to the public under the GNU GPL license. The standalone implementation can be found at http://github.com/EESI/Fizzy.« less

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.

UIVerify: A Web-Based Tool for Verification and Automatic Generation of User Interfaces

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Degani, Asaf; Heymann, Michael

2004-01-01

In this poster, we describe a web-based tool for verification and automatic generation of user interfaces. The verification component of the tool accepts as input a model of a machine and a model of its interface, and checks that the interface is adequate (correct). The generation component of the tool accepts a model of a given machine and the user's task, and then generates a correct and succinct interface. This write-up will demonstrate the usefulness of the tool by verifying the correctness of a user interface to a flight-control system. The poster will include two more examples of using the tool: verification of the interface to an espresso machine, and automatic generation of a succinct interface to a large hypothetical machine.

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.

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.

Variable Selection for Support Vector Machines in Moderately High Dimensions

PubMed Central

Zhang, Xiang; Wu, Yichao; Wang, Lan; Li, Runze

2015-01-01

Summary The support vector machine (SVM) is a powerful binary classification tool with high accuracy and great flexibility. It has achieved great success, but its performance can be seriously impaired if many redundant covariates are included. Some efforts have been devoted to studying variable selection for SVMs, but asymptotic properties, such as variable selection consistency, are largely unknown when the number of predictors diverges to infinity. In this work, we establish a unified theory for a general class of nonconvex penalized SVMs. We first prove that in ultra-high dimensions, there exists one local minimizer to the objective function of nonconvex penalized SVMs possessing the desired oracle property. We further address the problem of nonunique local minimizers by showing that the local linear approximation algorithm is guaranteed to converge to the oracle estimator even in the ultra-high dimensional setting if an appropriate initial estimator is available. This condition on initial estimator is verified to be automatically valid as long as the dimensions are moderately high. Numerical examples provide supportive evidence. PMID:26778916

Binary classification of aqueous solubility using support vector machines with reduction and recombination feature selection.

PubMed

Cheng, Tiejun; Li, Qingliang; Wang, Yanli; Bryant, Stephen H

2011-02-28

Aqueous solubility is recognized as a critical parameter in both the early- and late-stage drug discovery. Therefore, in silico modeling of solubility has attracted extensive interests in recent years. Most previous studies have been limited in using relatively small data sets with limited diversity, which in turn limits the predictability of derived models. In this work, we present a support vector machines model for the binary classification of solubility by taking advantage of the largest known public data set that contains over 46 000 compounds with experimental solubility. Our model was optimized in combination with a reduction and recombination feature selection strategy. The best model demonstrated robust performance in both cross-validation and prediction of two independent test sets, indicating it could be a practical tool to select soluble compounds for screening, purchasing, and synthesizing. Moreover, our work may be used for comparative evaluation of solubility classification studies ascribe to the use of completely public resources.

Selective laser sintering: A qualitative and objective approach

NASA Astrophysics Data System (ADS)

Kumar, Sanjay

2003-10-01

This article presents an overview of selective laser sintering (SLS) work as reported in various journals and proceedings. Selective laser sintering was first done mainly on polymers and nylon to create prototypes for audio-visual help and fit-to-form tests. Gradually it was expanded to include metals and alloys to manufacture functional prototypes and develop rapid tooling. The growth gained momentum with the entry of commercial entities such as DTM Corporation and EOS GmbH Electro Optical Systems. Computational modeling has been used to understand the SLS process, optimize the process parameters, and enhance the efficiency of the sintering machine.

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.

Underground coal mine instrumentation and test

NASA Technical Reports Server (NTRS)

Burchill, R. F.; Waldron, W. D.

1976-01-01

The need to evaluate mechanical performance of mine tools and to obtain test performance data from candidate systems dictate that an engineering data recording system be built. Because of the wide range of test parameters which would be evaluated, a general purpose data gathering system was designed and assembled to permit maximum versatility. A primary objective of this program was to provide a specific operating evaluation of a longwall mining machine vibration response under normal operating conditions. A number of mines were visited and a candidate for test evaluation was selected, based upon management cooperation, machine suitability, and mine conditions. Actual mine testing took place in a West Virginia mine.

The Gamma-Ray Burst ToolSHED is Open for Business

NASA Astrophysics Data System (ADS)

Giblin, Timothy W.; Hakkila, Jon; Haglin, David J.; Roiger, Richard J.

2004-09-01

The GRB ToolSHED, a Gamma-Ray Burst SHell for Expeditions in Data-Mining, is now online and available via a web browser to all in the scientific community. The ToolSHED is an online web utility that contains pre-processed burst attributes of the BATSE catalog and a suite of induction-based machine learning and statistical tools for classification and cluster analysis. Users create their own login account and study burst properties within user-defined multi-dimensional parameter spaces. Although new GRB attributes are periodically added to the database for user selection, the ToolSHED has a feature that allows users to upload their own burst attributes (e.g. spectral parameters, etc.) so that additional parameter spaces can be explored. A data visualization feature using GNUplot and web-based IDL has also been implemented to provide interactive plotting of user-selected session output. In an era in which GRB observations and attributes are becoming increasingly more complex, a utility such as the GRB ToolSHED may play an important role in deciphering GRB classes and understanding intrinsic burst properties.

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.

Feature selection and classification of protein-protein complexes based on their binding affinities using machine learning approaches.

PubMed

Yugandhar, K; Gromiha, M Michael

2014-09-01

Protein-protein interactions are intrinsic to virtually every cellular process. Predicting the binding affinity of protein-protein complexes is one of the challenging problems in computational and molecular biology. In this work, we related sequence features of protein-protein complexes with their binding affinities using machine learning approaches. We set up a database of 185 protein-protein complexes for which the interacting pairs are heterodimers and their experimental binding affinities are available. On the other hand, we have developed a set of 610 features from the sequences of protein complexes and utilized Ranker search method, which is the combination of Attribute evaluator and Ranker method for selecting specific features. We have analyzed several machine learning algorithms to discriminate protein-protein complexes into high and low affinity groups based on their Kd values. Our results showed a 10-fold cross-validation accuracy of 76.1% with the combination of nine features using support vector machines. Further, we observed accuracy of 83.3% on an independent test set of 30 complexes. We suggest that our method would serve as an effective tool for identifying the interacting partners in protein-protein interaction networks and human-pathogen interactions based on the strength of interactions. © 2014 Wiley Periodicals, Inc.

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

A hybrid algorithm optimization approach for machine loading problem in flexible manufacturing system

NASA Astrophysics Data System (ADS)

Kumar, Vijay M.; Murthy, ANN; Chandrashekara, K.

2012-05-01

The production planning problem of flexible manufacturing system (FMS) concerns with decisions that have to be made before an FMS begins to produce parts according to a given production plan during an upcoming planning horizon. The main aspect of production planning deals with machine loading problem in which selection of a subset of jobs to be manufactured and assignment of their operations to the relevant machines are made. Such problems are not only combinatorial optimization problems, but also happen to be non-deterministic polynomial-time-hard, making it difficult to obtain satisfactory solutions using traditional optimization techniques. In this paper, an attempt has been made to address the machine loading problem with objectives of minimization of system unbalance and maximization of throughput simultaneously while satisfying the system constraints related to available machining time and tool slot designing and using a meta-hybrid heuristic technique based on genetic algorithm and particle swarm optimization. The results reported in this paper demonstrate the model efficiency and examine the performance of the system with respect to measures such as throughput and system utilization.

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.

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

PubMed

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

2018-05-01

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

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2017-01-01

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

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.

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.

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

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…

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...

Applications of machine-learning algorithms for infrared colour selection of Galactic Wolf-Rayet stars

NASA Astrophysics Data System (ADS)

Morello, Giuseppe; Morris, P. W.; Van Dyk, S. D.; Marston, A. P.; Mauerhan, J. C.

2018-01-01

We have investigated and applied machine-learning algorithms for infrared colour selection of Galactic Wolf-Rayet (WR) candidates. Objects taken from the Spitzer Galactic Legacy Infrared Midplane Survey Extraordinaire (GLIMPSE) catalogue of the infrared objects in the Galactic plane can be classified into different stellar populations based on the colours inferred from their broad-band photometric magnitudes [J, H and Ks from 2 Micron All Sky Survey (2MASS), and the four Spitzer/IRAC bands]. The algorithms tested in this pilot study are variants of the k-nearest neighbours approach, which is ideal for exploratory studies of classification problems where interrelations between variables and classes are complicated. The aims of this study are (1) to provide an automated tool to select reliable WR candidates and potentially other classes of objects, (2) to measure the efficiency of infrared colour selection at performing these tasks and (3) to lay the groundwork for statistically inferring the total number of WR stars in our Galaxy. We report the performance results obtained over a set of known objects and selected candidates for which we have carried out follow-up spectroscopic observations, and confirm the discovery of four new WR stars.

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.

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.

“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

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

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

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…

Machine rates for selected forest harvesting machines

Treesearch

R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

2002-01-01

Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

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

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.

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.

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.

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

Fuzzy support vector machines for adaptive Morse code recognition.

PubMed

Yang, Cheng-Hong; Jin, Li-Cheng; Chuang, Li-Yeh

2006-11-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, facilitating mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. Therefore, an adaptive automatic recognition method with a high recognition rate is needed. The proposed system uses both fuzzy support vector machines and the variable-degree variable-step-size least-mean-square algorithm to achieve these objectives. We apply fuzzy memberships to each point, and provide different contributions to the decision learning function for support vector machines. Statistical analyses demonstrated that the proposed method elicited a higher recognition rate than other algorithms in the literature.

The Laser MicroJet (LMJ): a multi-solution technology for high quality micro-machining

NASA Astrophysics Data System (ADS)

Mai, Tuan Anh; Richerzhagen, Bernold; Snowdon, Paul C.; Wood, David; Maropoulos, Paul G.

2007-02-01

The field of laser micromachining is highly diverse. There are many different types of lasers available in the market. Due to their differences in irradiating wavelength, output power and pulse characteristic they can be selected for different applications depending on material and feature size [1]. The main issues by using these lasers are heat damages, contamination and low ablation rates. This report examines on the application of the Laser MicroJet(R) (LMJ), a unique combination of a laser beam with a hair-thin water jet as a universal tool for micro-machining of MEMS substrates, as well as ferrous and non-ferrous materials. The materials include gallium arsenide (GaAs) & silicon wafers, steel, tantalum and alumina ceramic. A Nd:YAG laser operating at 1064 nm (infra red) and frequency doubled 532 nm (green) were employed for the micro-machining of these materials.

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.

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.

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

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.

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.

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...

Effect of rotation speed and welding speed on Friction Stir Welding of AA1100 Aluminium alloy

NASA Astrophysics Data System (ADS)

Raja, P.; Bojanampati, S.; Karthikeyan, R.; Ganithi, R.

2018-04-01

Aluminum AA1100 is the most widely used grade of Aluminium due to its excellent corrosion resistance, high ductility and reflective finish, the selected material was welded with Friction Stir Welding (FSW) process on a CNC machine, using a combination of different tool rotation speed (1500 rpm, 2500 rpm, 3500 rpm) and welding speed (10 mm/min, 30 mm/min, 50 mm/min) as welding parameters. The effect of FSW using this welding parameter was studied by measuring the ultimate tensile strength of the welded joints. A high-speed steel tool was prepared for welding the Aluminium AA1100 alloy having an 8mm shoulder diameter and pin dimension of 4mm diameter and 2.8 mm length. The welded joints were tested using the universal testing machine. It was found that Ultimate Tensile Strength of FSW specimen was highest with a value of 98.08 MPa when the weld was performed at rotation speed of 1500 RPM and welding speed of 50 mm/min.

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

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.

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.

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.

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.

Virtual screening of selective multitarget kinase inhibitors by combinatorial support vector machines.

PubMed

Ma, X H; Wang, R; Tan, C Y; Jiang, Y Y; Lu, T; Rao, H B; Li, X Y; Go, M L; Low, B C; Chen, Y Z

2010-10-04

Multitarget agents have been increasingly explored for enhancing efficacy and reducing countertarget activities and toxicities. Efficient virtual screening (VS) tools for searching selective multitarget agents are desired. Combinatorial support vector machines (C-SVM) were tested as VS tools for searching dual-inhibitors of 11 combinations of 9 anticancer kinase targets (EGFR, VEGFR, PDGFR, Src, FGFR, Lck, CDK1, CDK2, GSK3). C-SVM trained on 233-1,316 non-dual-inhibitors correctly identified 26.8%-57.3% (majority >36%) of the 56-230 intra-kinase-group dual-inhibitors (equivalent to the 50-70% yields of two independent individual target VS tools), and 12.2% of the 41 inter-kinase-group dual-inhibitors. C-SVM were fairly selective in misidentifying as dual-inhibitors 3.7%-48.1% (majority <20%) of the 233-1,316 non-dual-inhibitors of the same kinase pairs and 0.98%-4.77% of the 3,971-5,180 inhibitors of other kinases. C-SVM produced low false-hit rates in misidentifying as dual-inhibitors 1,746-4,817 (0.013%-0.036%) of the 13.56 M PubChem compounds, 12-175 (0.007%-0.104%) of the 168 K MDDR compounds, and 0-84 (0.0%-2.9%) of the 19,495-38,483 MDDR compounds similar to the known dual-inhibitors. C-SVM was compared to other VS methods Surflex-Dock, DOCK Blaster, kNN and PNN against the same sets of kinase inhibitors and the full set or subset of the 1.02 M Zinc clean-leads data set. C-SVM produced comparable dual-inhibitor yields, slightly better false-hit rates for kinase inhibitors, and significantly lower false-hit rates for the Zinc clean-leads data set. Combinatorial SVM showed promising potential for searching selective multitarget agents against intra-kinase-group kinases without explicit knowledge of multitarget agents.

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.

Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis.

PubMed

Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra

2014-01-01

Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. The aims were to describe how to:(i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and(ii) automatically identify the features that best distinguish the groups. The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described - simple or complex; presentation order - which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo 18 were used,which included 200 healthy Brazilians of both genders. A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods.

Development of materials for the rapid manufacture of die cast tooling

NASA Astrophysics Data System (ADS)

Hardro, Peter Jason

The focus of this research is to develop a material composition that can be processed by rapid prototyping (RP) in order to produce tooling for the die casting process. Where these rapidly produced tools will be superior to traditional tooling production methods by offering one or more of the following advantages: reduced tooling cost, shortened tooling creation time, reduced man-hours for tool creation, increased tool life, and shortened die casting cycle time. By utilizing RP's additive build process and vast material selection, there was a prospect that die cast tooling may be produced quicker and with superior material properties. To this end, the material properties that influence die life and cycle time were determined, and a list of materials that fulfill these "optimal" properties were highlighted. Physical testing was conducted in order to grade the processability of each of the material systems and to optimize the manufacturing process for the downselected material system. Sample specimens were produced and microscopy techniques were utilized to determine a number of physical properties of the material system. Additionally, a benchmark geometry was selected and die casting dies were produced from traditional tool materials (H13 steel) and techniques (machining) and from the newly developed materials and RP techniques (selective laser sintering (SLS) and laser engineered net shaping (LENS)). Once the tools were created, a die cast alloy was selected and a preset number of parts were shot into each tool. During tool creation, the manufacturing time and cost was closely monitored and an economic model was developed to compare traditional tooling to RP tooling. This model allows one to determine, in the early design stages, when it is advantageous to implement RP tooling and when traditional tooling would be best. The results of the physical testing and economic analysis has shown that RP tooling is able to achieve a number of the research objectives, namely, reduce tooling cost, shorten tooling creation time, and reduce the man-hours needed for tool creation. Though identifying the appropriate time to use RP tooling appears to be the most important aspect in achieving successful implementation.

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.

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

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.…

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.

[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.

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.

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.

Approach to in-process tool wear monitoring in drilling: Application of Kalman filter theory

NASA Astrophysics Data System (ADS)

He, Ning; Zhang, Youzhen; Pan, Liangxian

1993-05-01

The two parameters often used in adaptive control, tool wear and wear rate, are the important factors affecting machinability. In this paper, it is attempted to use the modern cybernetics to solve the in-process tool wear monitoring problem by applying the Kalman filter theory to monitor drill wear quantitatively. Based on the experimental results, a dynamic model, a measuring model and a measurement conversion model suitable for Kalman filter are established. It is proved that the monitoring system possesses complete observability but does not possess complete controllability. A discriminant for selecting the characteristic parameters is put forward. The thrust force Fz is selected as the characteristic parameter in monitoring the tool wear by this discriminant. The in-process Kalman filter drill wear monitoring system composed of force sensor microphotography and microcomputer is well established. The results obtained by the Kalman filter, the common indirect measuring method and the real drill wear measured by the aid of microphotography are compared. The result shows that the Kalman filter has high precision of measurement and the real time requirement can be satisfied.

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.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

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…

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

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.

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.

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).

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.

Multi-Cultural Competency-Based Vocational Curricula. Machine Trades. Multi-Cultural Competency-Based Vocational/Technical Curricula Series.

ERIC Educational Resources Information Center

Hepburn, Larry; Shin, Masako

This document, one of eight in a multi-cultural competency-based vocational/technical curricula series, is on machine trades. This program is designed to run 36 weeks and cover 6 instructional areas: use of measuring tools; benchwork/tool bit grinding; lathe work; milling work; precision grinding; and combination machine work. A duty-task index…

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.

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.

Software component quality evaluation

NASA Technical Reports Server (NTRS)

Clough, A. J.

1991-01-01

The paper describes a software inspection process that can be used to evaluate the quality of software components. Quality criteria, process application, independent testing of the process and proposed associated tool support are covered. Early results indicate that this technique is well suited for assessing software component quality in a standardized fashion. With automated machine assistance to facilitate both the evaluation and selection of software components, such a technique should promote effective reuse of software components.

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.

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.

MULTIPLE SHAFT TOOL HEAD

DOEpatents

Colbert, H.P.

1962-10-23

An improved tool head arrangement is designed for the automatic expanding of a plurality of ferruled tubes simultaneously. A plurality of output shafts of a multiple spindle drill head are driven in unison by a hydraulic motor. A plurality of tube expanders are respectively coupled to the shafts through individual power train arrangements. The axial or thrust force required for the rolling operation is provided by a double acting hydraulic cylinder having a hollow through shaft with the shaft cooperating with an internally rotatable splined shaft slidably coupled to a coupling rigidly attached to the respectlve output shaft of the drill head, thereby transmitting rotary motion and axial thrust simultaneously to the tube expander. A hydraulic power unit supplies power to each of the double acting cylinders through respective two-position, four-way valves, under control of respective solenoids for each of the cylinders. The solenoids are in turn selectively controlled by a tool selection control unit which in turn is controlled by signals received from a programmed, coded tape from a tape reader. The number of expanders that are extended in a rolling operation, which may be up to 42 expanders, is determined by a predetermined program of operations depending upon the arrangement of the ferruled tubes to be expanded in the tube bundle. The tape reader also supplies dimensional information to a machine tool servo control unit for imparting selected, horizontal and/or vertical movement to the tool head assembly. (AEC)

An Examination of Selected Software Testing Tools: 1993 Supplement

DTIC Science & Technology

1993-10-01

tool users. They have recently established a relationship with a U.S. company, Texel & Co., who will market and support AdaTEST in this country. AdaTEST...was first marketed in 1991 and is now used at more than 15 sites internationally. It is machine and operating system independent, relying only on the...uin~ ugc ~zin~f224.64 N&MOSNOtRaD.YC 625.36, O •OMamm c 0.26 MZ~jVJO~ZAL.WW .00 mISIW...2aV3...OW.)b!UWZOU0.01mu.muw...mnav._ohawM3C2Ut’c 0.04 ,85152.88

Design selection of an innovative tool holder for ultrasonic vibration assisted turning (IN-UVAT) using finite element analysis simulation

NASA Astrophysics Data System (ADS)

Rachmat, Haris; Ibrahim, M. Rasidi; Hasan, Sulaiman bin

2017-04-01

On of high technology in machining is ultrasonic vibration assisted turning. The design of tool holder was a crucial step to make sure the tool holder is enough to handle all forces on turning process. Because of the direct experimental approach is expensive, the paper studied to predict feasibility of tool holder displacement and effective stress was used the computational in finite element simulation. SS201 and AISI 1045 materials were used with sharp and ramp corners flexure hinges on design. The result shows that AISI 1045 material and which has ramp corner flexure hinge was the best choice to be produced. The displacement is around 11.3 micron and effective stress is 1.71e+008 N/m2 and also the factor of safety is 3.10.

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.

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.

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

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.

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.

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.

A clinical risk stratification tool for predicting treatment resistance in major depressive disorder.

PubMed

Perlis, Roy H

2013-07-01

Early identification of depressed individuals at high risk for treatment resistance could be helpful in selecting optimal setting and intensity of care. At present, validated tools to facilitate this risk stratification are rarely used in psychiatric practice. Data were drawn from the first two treatment levels of a multicenter antidepressant effectiveness study in major depressive disorder, the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) cohort. This cohort was divided into training, testing, and validation subsets. Only clinical or sociodemographic variables available by or readily amenable to self-report were considered. Multivariate models were developed to discriminate individuals reaching remission with a first or second pharmacological treatment trial from those not reaching remission despite two trials. A logistic regression model achieved an area under the receiver operating characteristic curve exceeding .71 in training, testing, and validation cohorts and maintained good calibration across cohorts. Performance of three alternative models with machine learning approaches--a naïve Bayes classifier and a support vector machine, and a random forest model--was less consistent. Similar performance was observed between more and less severe depression, men and women, and primary versus specialty care sites. A web-based calculator was developed that implements this tool and provides graphical estimates of risk. Risk for treatment resistance among outpatients with major depressive disorder can be estimated with a simple model incorporating baseline sociodemographic and clinical features. Future studies should examine the performance of this model in other clinical populations and its utility in treatment selection or clinical trial design. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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.

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

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

Factors that affect micro-tooling features created by direct printing approach

NASA Astrophysics Data System (ADS)

Kumbhani, Mayur N.

Current market required faster pace production of smaller, better, and improved products in shorter amount of time. Traditional high-rate manufacturing process such as hot embossing, injection molding, compression molding, etc. use tooling to replicate feature on a products. Miniaturization of many product in the field of biomedical, electronics, optical, and microfluidic is occurring on a daily bases. There is a constant need to produce cheaper, and faster tooling, which can be utilize by existing manufacturing processes. Traditionally, in order to manufacture micron size tooling features processes such as micro-machining, Electrical Discharge Machining (EDM), etc. are utilized. Due to a higher difficulty to produce smaller size features, and longer production cycle time, various additive manufacturing approaches are proposed, e.g. selective laser sintering (SLS), inkjet printing (3DP), fused deposition modeling (FDM), etc. were proposed. Most of these approaches can produce net shaped products from different materials such as metal, ceramic, or polymers. Several attempts were made to produce tooling features using additive manufacturing approaches. Most of these produced tooling were not cost effective, and the life cycle of these tooling was reported short. In this research, a method to produce tooling features using direct printing approach, where highly filled feedstock was dispensed on a substrate. This research evaluated different natural binders, such as guar gum, xanthan gum, and sodium carboxymethyl cellulose (NaCMC) and their combinations were evaluated. The best binder combination was then use to evaluate effect of different metal (316L stainless steel (3 mum), 316 stainless steel (45 mum), and 304 stainless steel (45 mum)) particle size on feature quality. Finally, the effect of direct printing process variables such as dispensing tip internal diameter (500 mum, and 333 mum) at different printing speeds were evaluated.

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.

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.

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

Disk Rock Cutting Tool for the Implementation of Resource-Saving Technologies of Mining of Solid Minerals

NASA Astrophysics Data System (ADS)

Manietyev, Leonid; Khoreshok, Aleksey; Tsekhin, Alexander; Borisov, Andrey

2017-11-01

The directions of a resource and energy saving when creating a boom-type effectors of roadheaders of selective action with disc rock cutting tools on a multi-faceted prisms for the destruction of formation of minerals and rocks pricemax are presented. Justified reversing the modes of the crowns and booms to improve the efficiency of mining works. Parameters of destruction of coal and rock faces by the disk tool of a biconical design with the unified fastening knots to many-sided prisms on effectors of extraction mining machines are determined. Parameters of tension of the interfaced elements of knots of fastening of the disk tool at static interaction with the destroyed face of rocks are set. The technical solutions containing the constructive and kinematic communications realizing counter and reverse mode of rotation of two radial crowns with the disk tool on trihedral prisms and cases of booms with the disk tool on tetrahedral prisms in internal space between two axial crowns with the cutter are proposed. Reserves of expansion of the front of loading outside a table of a feeder of the roadheader of selective action, including side zones in which loading corridors by blades of trihedral prisms in internal space between two radial crowns are created are revealed.

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.

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.

Mechanization for Optimal Landscape Reclamation

NASA Astrophysics Data System (ADS)

Vondráčková, Terezie; Voštová, Věra; Kraus, Michal

2017-12-01

Reclamation is a method of ultimate utilization of land adversely affected by mining or other industrial activity. The paper explains the types of reclamation and the term “optimal reclamation”. Technological options of the long-lasting process of mine dumps reclamation starting with the removal of overlying rocks, transport and backfilling up to the follow-up remodelling of the mine dumps terrain. Technological units and equipment for stripping flow division. Stripping flow solution with respect to optimal reclamation. We recommend that the application of logistic chains and mining simulation with follow-up reclamation to open-pit mines be used for the implementation of optimal reclamation. In addition to a database of local heterogeneities of the stripped soil and reclaimed land, the flow of earths should be resolved in a manner allowing the most suitable soil substrate to be created for the restoration of agricultural and forest land on mine dumps. The methodology under development for the solution of a number of problems, including the geological survey of overlying rocks, extraction of stripping, their transport and backfilling in specified locations with the follow-up deployment of goal-directed reclamation. It will make possible to reduce the financial resources needed for the complex process chain by utilizing GIS, GPS and DGPS technologies, logistic tools and synergistic effects. When selecting machines for transport, moving and spreading of earths, various points of view and aspects must be taken into account. Among such aspects are e.g. the kind of earth to be operated by the respective construction machine, the kind of work activities to be performed, the machine’s capacity, the option to control the machine’s implement and economic aspects and clients’ requirements. All these points of view must be considered in the decision-making process so that the selected machine is capable of executing the required activity and that the use of an unsuitable machine is eliminated as it would result in a delay and increase in the project costs. Therefore, reclamation always includes extensive earth-moving work activities restoring the required relief of the land being reclaimed. Using the earth-moving machine capacity, the kind of soil in mine dumps, the kind of the work activity performed and the machine design, a SW application has been developed that allows the most suitable machine for the respective work technology to be selected with a view to preparing the land intended for reclamation.

Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

PubMed Central

Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

2016-01-01

The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

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.

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.

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…

Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.

PubMed

Armañanzas, Rubén; Alonso-Nanclares, Lidia; Defelipe-Oroquieta, Jesús; Kastanauskaite, Asta; de Sola, Rafael G; Defelipe, Javier; Bielza, Concha; Larrañaga, Pedro

2013-01-01

Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE). Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of epilepsy surgery based on supervised classification data mining taking into account not only the common clinical variables, but also pathological and neuropsychological evaluations. We have generated models capable of predicting whether a patient with TLE secondary to hippocampal sclerosis will fully recover from epilepsy or not. The machine learning analysis revealed that outcome could be predicted with an estimated accuracy of almost 90% using some clinical and neuropsychological features. Importantly, not all the features were needed to perform the prediction; some of them proved to be irrelevant to the prognosis. Personality style was found to be one of the key features to predict the outcome. Although we examined relatively few cases, findings were verified across all data, showing that the machine learning approach described in the present study may be a powerful method. Since neuropsychological assessment of epileptic patients is a standard protocol in the pre-surgical evaluation, we propose to include these specific psychological tests and machine learning tools to improve the selection of candidates for epilepsy surgery.

Machine Learning Approach for the Outcome Prediction of Temporal Lobe Epilepsy Surgery

PubMed Central

DeFelipe-Oroquieta, Jesús; Kastanauskaite, Asta; de Sola, Rafael G.; DeFelipe, Javier; Bielza, Concha; Larrañaga, Pedro

2013-01-01

Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE). Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of epilepsy surgery based on supervised classification data mining taking into account not only the common clinical variables, but also pathological and neuropsychological evaluations. We have generated models capable of predicting whether a patient with TLE secondary to hippocampal sclerosis will fully recover from epilepsy or not. The machine learning analysis revealed that outcome could be predicted with an estimated accuracy of almost 90% using some clinical and neuropsychological features. Importantly, not all the features were needed to perform the prediction; some of them proved to be irrelevant to the prognosis. Personality style was found to be one of the key features to predict the outcome. Although we examined relatively few cases, findings were verified across all data, showing that the machine learning approach described in the present study may be a powerful method. Since neuropsychological assessment of epileptic patients is a standard protocol in the pre-surgical evaluation, we propose to include these specific psychological tests and machine learning tools to improve the selection of candidates for epilepsy surgery. PMID:23646148

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.

miREE: miRNA recognition elements ensemble

PubMed Central

2011-01-01

Background Computational methods for microRNA target prediction are a fundamental step to understand the miRNA role in gene regulation, a key process in molecular biology. In this paper we present miREE, a novel microRNA target prediction tool. miREE is an ensemble of two parts entailing complementary but integrated roles in the prediction. The Ab-Initio module leverages upon a genetic algorithmic approach to generate a set of candidate sites on the basis of their microRNA-mRNA duplex stability properties. Then, a Support Vector Machine (SVM) learning module evaluates the impact of microRNA recognition elements on the target gene. As a result the prediction takes into account information regarding both miRNA-target structural stability and accessibility. Results The proposed method significantly improves the state-of-the-art prediction tools in terms of accuracy with a better balance between specificity and sensitivity, as demonstrated by the experiments conducted on several large datasets across different species. miREE achieves this result by tackling two of the main challenges of current prediction tools: (1) The reduced number of false positives for the Ab-Initio part thanks to the integration of a machine learning module (2) the specificity of the machine learning part, obtained through an innovative technique for rich and representative negative records generation. The validation was conducted on experimental datasets where the miRNA:mRNA interactions had been obtained through (1) direct validation where even the binding site is provided, or through (2) indirect validation, based on gene expression variations obtained from high-throughput experiments where the specific interaction is not validated in detail and consequently the specific binding site is not provided. Conclusions The coupling of two parts: a sensitive Ab-Initio module and a selective machine learning part capable of recognizing the false positives, leads to an improved balance between sensitivity and specificity. miREE obtains a reasonable trade-off between filtering false positives and identifying targets. miREE tool is available online at http://didattica-online.polito.it/eda/miREE/ PMID:22115078

Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis

PubMed Central

Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra

2014-01-01

Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. Objective The aims were to describe how to: (i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and (ii) automatically identify the features that best distinguish the groups. Methods The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described – simple or complex; presentation order – which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo18 were used,which included 200 healthy Brazilians of both genders. Results and Conclusion A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods. PMID:29213908

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.

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 Study on Human Oriented Autonomous Distributed Manufacturing System —Real-time Scheduling Method Based on Preference of Human Operators

NASA Astrophysics Data System (ADS)

Iwamura, Koji; Kuwahara, Shinya; Tanimizu, Yoshitaka; Sugimura, Nobuhiro

Recently, new distributed architectures of manufacturing systems are proposed, aiming at realizing more flexible control structures of the manufacturing systems. Many researches have been carried out to deal with the distributed architectures for planning and control of the manufacturing systems. However, the human operators have not yet been discussed for the autonomous components of the distributed manufacturing systems. A real-time scheduling method is proposed, in this research, to select suitable combinations of the human operators, the resources and the jobs for the manufacturing processes. The proposed scheduling method consists of following three steps. In the first step, the human operators select their favorite manufacturing processes which they will carry out in the next time period, based on their preferences. In the second step, the machine tools and the jobs select suitable combinations for the next machining processes. In the third step, the automated guided vehicles and the jobs select suitable combinations for the next transportation processes. The second and third steps are carried out by using the utility value based method and the dispatching rule-based method proposed in the previous researches. Some case studies have been carried out to verify the effectiveness of the proposed method.

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.

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.

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.

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

PubMed

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Möller, Steffen; Hartmann, Enno; Kalies, Kai-Uwe; Suganthan, P N; Martinetz, Thomas

2010-12-01

Apoptosis is an essential process for controlling tissue homeostasis by regulating a physiological balance between cell proliferation and cell death. The subcellular locations of proteins performing the cell death are determined by mostly independent cellular mechanisms. The regular bioinformatics tools to predict the subcellular locations of such apoptotic proteins do often fail. This work proposes a model for the sorting of proteins that are involved in apoptosis, allowing us to both the prediction of their subcellular locations as well as the molecular properties that contributed to it. We report a novel hybrid Genetic Algorithm (GA)/Support Vector Machine (SVM) approach to predict apoptotic protein sequences using 119 sequence derived properties like frequency of amino acid groups, secondary structure, and physicochemical properties. GA is used for selecting a near-optimal subset of informative features that is most relevant for the classification. Jackknife cross-validation is applied to test the predictive capability of the proposed method on 317 apoptosis proteins. Our method achieved 85.80% accuracy using all 119 features and 89.91% accuracy for 25 features selected by GA. Our models were examined by a test dataset of 98 apoptosis proteins and obtained an overall accuracy of 90.34%. The results show that the proposed approach is promising; it is able to select small subsets of features and still improves the classification accuracy. Our model can contribute to the understanding of programmed cell death and drug discovery. The software and dataset are available at http://www.inb.uni-luebeck.de/tools-demos/apoptosis/GASVM.

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.

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.

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach.

PubMed

Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D; Duvenaud, David; Maclaurin, Dougal; Blood-Forsythe, Martin A; Chae, Hyun Sik; Einzinger, Markus; Ha, Dong-Gwang; Wu, Tony; Markopoulos, Georgios; Jeon, Soonok; Kang, Hosuk; Miyazaki, Hiroshi; Numata, Masaki; Kim, Sunghan; Huang, Wenliang; Hong, Seong Ik; Baldo, Marc; Adams, Ryan P; Aspuru-Guzik, Alán

2016-10-01

Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.

Modeling of power transmission and stress grading for corona protection

NASA Astrophysics Data System (ADS)

Zohdi, T. I.; Abali, B. E.

2017-11-01

Electrical high voltage (HV) machines are prone to corona discharges leading to power losses as well as damage of the insulating layer. Many different techniques are applied as corona protection and computational methods aid to select the best design. In this paper we develop a reduced-order model in 1D estimating electric field and temperature distribution of a conductor wrapped with different layers, as usual for HV-machines. Many assumptions and simplifications are undertaken for this 1D model, therefore, we compare its results to a direct numerical simulation in 3D quantitatively. Both models are transient and nonlinear, giving a possibility to quickly estimate in 1D or fully compute in 3D by a computational cost. Such tools enable understanding, evaluation, and optimization of corona shielding systems for multilayered coils.

Census of the Local Universe (CLU): Classification of Galaxy Candidates in Narrowband Images Using Machine Learning

NASA Astrophysics Data System (ADS)

Zhang, Chaoran; Van Sistine, Anglea; Kaplan, David; Brady, Patrick; Cook, David O.; Kasliwal, Mansi

2018-01-01

A complete catalog of galaxies in the local universe is critical for efficient electromagnetic follow-up of gravitational wave events (EMGW). The Census of the Local Universe (CLU; Cook et al. 2017, in preparation) aims to provide a galaxy catalog out to 200 Mpc that is as complete as possible. CLU has recently completed an Hα survey of ~3π of the sky with the goal of cataloging those galaxies that are likely hosts of EMGW events. Here, we present a tool we developed using machine learning technology to classify sources extracted from the Hα narrowband images within 200Mpc. In this analysis we find we are able to recover more galaxies compared to selections based on Hα colors alone.

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

NASA Astrophysics Data System (ADS)

Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D.; Duvenaud, David; MacLaurin, Dougal; Blood-Forsythe, Martin A.; Chae, Hyun Sik; Einzinger, Markus; Ha, Dong-Gwang; Wu, Tony; Markopoulos, Georgios; Jeon, Soonok; Kang, Hosuk; Miyazaki, Hiroshi; Numata, Masaki; Kim, Sunghan; Huang, Wenliang; Hong, Seong Ik; Baldo, Marc; Adams, Ryan P.; Aspuru-Guzik, Alán

2016-10-01

Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.

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.

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

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.

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.

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.

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.

Data Mining and Machine Learning in Astronomy

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Brunner, Robert J.

We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. However, if misused, it can be little more than the black box application of complex computing algorithms that may give little physical insight, and provide questionable results. Here, we give an overview of the entire data mining process, from data collection through to the interpretation of results. We cover common machine learning algorithms, such as artificial neural networks and support vector machines, applications from a broad range of astronomy, emphasizing those in which data mining techniques directly contributed to improving science, and important current and future directions, including probability density functions, parallel algorithms, Peta-Scale computing, and the time domain. We conclude that, so long as one carefully selects an appropriate algorithm and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.

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;…

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

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.

Vending machine assessment methodology. A systematic review.

PubMed

Matthews, Melissa A; Horacek, Tanya M

2015-07-01

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

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.

Effect of micro-scale texturing on the cutting tool performance

NASA Astrophysics Data System (ADS)

Vasumathy, D.; Meena, Anil

2018-05-01

The present study is mainly focused on the cutting performance of the micro-scale textured carbide tools while turning AISI 304 austenitic stainless steel under dry cutting environment. The texture on the rake face of the carbide tools was fabricated by laser machining. The cutting performance of the textured tools was further compared with conventional tools in terms of cutting forces, tool wear, machined surface quality and chip curl radius. SEM and EDS analyses have been also performed to better understand the tool surface characteristics. Results show that the grooves help in breaking the tool-chip contact leading to a lesser tool-chip contact area which results in reduced iron (Fe) adhesion to the tool.

Machinability of IPS Empress 2 framework ceramic.

PubMed

Schmidt, C; Weigl, P

2000-01-01

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

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.

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.

Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients.

PubMed

Cangelosi, Davide; Muselli, Marco; Parodi, Stefano; Blengio, Fabiola; Becherini, Pamela; Versteeg, Rogier; Conte, Massimo; Varesio, Luigi

2014-01-01

Cancer patient's outcome is written, in part, in the gene expression profile of the tumor. We previously identified a 62-probe sets signature (NB-hypo) to identify tissue hypoxia in neuroblastoma tumors and showed that NB-hypo stratified neuroblastoma patients in good and poor outcome 1. It was important to develop a prognostic classifier to cluster patients into risk groups benefiting of defined therapeutic approaches. Novel classification and data discretization approaches can be instrumental for the generation of accurate predictors and robust tools for clinical decision support. We explored the application to gene expression data of Rulex, a novel software suite including the Attribute Driven Incremental Discretization technique for transforming continuous variables into simplified discrete ones and the Logic Learning Machine model for intelligible rule generation. We applied Rulex components to the problem of predicting the outcome of neuroblastoma patients on the bases of 62 probe sets NB-hypo gene expression signature. The resulting classifier consisted in 9 rules utilizing mainly two conditions of the relative expression of 11 probe sets. These rules were very effective predictors, as shown in an independent validation set, demonstrating the validity of the LLM algorithm applied to microarray data and patients' classification. The LLM performed as efficiently as Prediction Analysis of Microarray and Support Vector Machine, and outperformed other learning algorithms such as C4.5. Rulex carried out a feature selection by selecting a new signature (NB-hypo-II) of 11 probe sets that turned out to be the most relevant in predicting outcome among the 62 of the NB-hypo signature. Rules are easily interpretable as they involve only few conditions. Our findings provided evidence that the application of Rulex to the expression values of NB-hypo signature created a set of accurate, high quality, consistent and interpretable rules for the prediction of neuroblastoma patients' outcome. We identified the Rulex weighted classification as a flexible tool that can support clinical decisions. For these reasons, we consider Rulex to be a useful tool for cancer classification from microarray gene expression data.

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

Using machine learning for sequence-level automated MRI protocol selection in neuroradiology.

PubMed

Brown, Andrew D; Marotta, Thomas R

2018-05-01

Incorrect imaging protocol selection can lead to important clinical findings being missed, contributing to both wasted health care resources and patient harm. We present a machine learning method for analyzing the unstructured text of clinical indications and patient demographics from magnetic resonance imaging (MRI) orders to automatically protocol MRI procedures at the sequence level. We compared 3 machine learning models - support vector machine, gradient boosting machine, and random forest - to a baseline model that predicted the most common protocol for all observations in our test set. The gradient boosting machine model significantly outperformed the baseline and demonstrated the best performance of the 3 models in terms of accuracy (95%), precision (86%), recall (80%), and Hamming loss (0.0487). This demonstrates the feasibility of automating sequence selection by applying machine learning to MRI orders. Automated sequence selection has important safety, quality, and financial implications and may facilitate improvements in the quality and safety of medical imaging service delivery.

Technical Report on Occupations in Numerically Controlled Metal-Cutting Machining.

ERIC Educational Resources Information Center

Manpower Administration (DOL), Washington, DC. U.S. Employment Service.

At the present time, only 5 percent of the short-run metal-cutting machining in the United States is done by numerically controlled machined tools, but within the next decade it is expected to increase by 50 percent. Numerically controlled machines use taped data which is changed into instructions and directs the machine to do certain steps…

Sine-Bar Attachment For Machine Tools

NASA Technical Reports Server (NTRS)

Mann, Franklin D.

1988-01-01

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

Method and device for determining the position of a cutting tool relative to the rotational axis of a spindle-mounted workpiece

DOEpatents

Williams, R.R.

1980-09-03

The present invention is directed to a method and device for determining the location of a cutting tool with respect to the rotational axis of a spindle-mounted workpiece. A vacuum cup supporting a machinable sacrificial pin is secured to the workpiece at a location where the pin will project along and encompass the rotational axis of the workpiece. The pin is then machined into a cylinder. The position of the surface of the cutting tool contacting the machine cylinder is spaced from the rotational axis of the workpiece a distance equal to the radius of the cylinder.

Method and device for determining the position of a cutting tool relative to the rotational axis of a spindle-mounted workpiece

DOEpatents

Williams, Richard R.

1982-01-01

The present invention is directed to a method and device for determining the location of a cutting tool with respect to the rotational axis of a spindle-mounted workpiece. A vacuum cup supporting a machinable sacrifical pin is secured to the workpiece at a location where the pin will project along and encompass the rotational axis of the workpiece. The pin is then machined into a cylinder. The position of the surface of the cutting tool contacting the machine cylinder is spaced from the rotational aixs of the workpiece a distance equal to the radius of the cylinder.

Investigation of approximate models of experimental temperature characteristics of machines

NASA Astrophysics Data System (ADS)

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

2018-05-01

This work is devoted to the investigation of various approaches to the approximation of experimental data and the creation of simulation mathematical models of thermal processes in machines with the aim of finding ways to reduce the time of their field tests and reducing the temperature error of the treatments. The main methods of research which the authors used in this work are: the full-scale thermal testing of machines; realization of various approaches at approximation of experimental temperature characteristics of machine tools by polynomial models; analysis and evaluation of modelling results (model quality) of the temperature characteristics of machines and their derivatives up to the third order in time. As a result of the performed researches, rational methods, type, parameters and complexity of simulation mathematical models of thermal processes in machine tools are proposed.

High performance cutting using micro-textured tools and low pressure jet coolant

NASA Astrophysics Data System (ADS)

Obikawa, Toshiyuki; Nakatsukasa, Ryuta; Hayashi, Mamoru; Ohno, Tatsumi

2018-05-01

Tool inserts with different kinds of microtexture on the flank face were fabricated by laser irradiation for promoting the heat transfer from the tool face to the coolant. In addition to the micro-textured tools, jet coolant was applied to the tool tip from the side of the flank face, but under low-pressure conditions, to make Reynolds number of coolant as high as possible in the wedge shape zone between the tool flank and machined surface. First, the effect of jet coolant on the flank wear evolution was investigated using a tool without microtexture. The jet coolant showed an excellent improvement of the tool life in machining stainless steel SUS304 at higher cutting speeds. It was found that both the flow rate and velocity of jet coolant were indispensable to high performance cutting. Next, the effect of microtexture on the flank wear evolution was investigated using jet coolant. Three types of micro grooves extended tool life largely compared to the tool without microtexture. It was found that the depth of groove was one of important parameters affecting the tool life extension. As a result, the tool life was extended by more than l00 % using the microtextured tools and jet coolant compared to machining using flood coolant and a tool without microtexture.

Multisensor systems today and tomorrow: Machine control, diagnosis and thermal compensation

NASA Astrophysics Data System (ADS)

Nunzio, D'Addea

2000-05-01

Multisensor techniques that deal with control of tribology test rig and with diagnosis and thermal error compensation of machine tools are the starting point for some consideration about the use of these techniques as in fuzzy and neural net systems. The author comes to conclusion that anticipatory systems and multisensor techniques will have in the next future a great improvement and a great development mainly in the thermal error compensation of machine tools.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Experimental study on internal cooling system in hard turning of HCWCI using CBN tools

NASA Astrophysics Data System (ADS)

Ravi, A. M.; Murigendrappa, S. M.

2018-04-01

In recent times, hard turning became most emerging technique in manufacturing processes, especially to cut high hard materials like high chrome white cast iron (HCWCI). Use of Cubic boron nitride (CBN), pCBN and Carbide tools are most appropriate to shear the metals but are uneconomical. Since hard turning carried out in dry condition, lowering the tool wear by minimizing tool temperature is the only solution. Study reveals, no effective cooling systems are available so for in order to enhance the tool life of the cutting tools and to improve machinability characteristics. The detrimental effect of cutting parameters on cutting temperature is generally controlled by proper selections. The objective of this paper is to develop a new cooling system to control tool tip temperature, thereby minimizing the cutting forces and the tool wear rates. The materials chosen for this work was HCWCI and cutting tools are CBN inserts. Intricate cavities were made on the periphery of the tool holder for easy flow of cold water. Taguchi techniques were adopted to carry out the experimentations. The experimental results confirm considerable reduction in the cutting forces and tool wear rates.

Methodology for identifying and representing knowledge in the scope of CMM inspection resource selection

NASA Astrophysics Data System (ADS)

Martínez, S.; Barreiro, J.; Cuesta, E.; Álvarez, B. J.; González, D.

2012-04-01

This paper is focused on the task of elicitation and structuring of knowledge related to selection of inspection resources. The final goal is to obtain an informal model of knowledge oriented to the inspection planning in coordinate measuring machines. In the first tasks, where knowledge is captured, it is necessary to use tools that make easier the analysis and structuring of knowledge, so that rules of selection can be easily stated to configure the inspection resources. In order to store the knowledge a so-called Onto-Process ontology has been developed. This ontology may be of application to diverse processes in manufacturing engineering. This paper describes the decomposition of the ontology in terms of general units of knowledge and others more specific for selection of sensor assemblies in inspection planning with touch sensors.

Comparative Investigation on Tool Wear during End Milling of AISI H13 Steel with Different Tool Path Strategies

NASA Astrophysics Data System (ADS)

Adesta, Erry Yulian T.; Riza, Muhammad; Avicena

2018-03-01

Tool wear prediction plays a significant role in machining industry for proper planning and control machining parameters and optimization of cutting conditions. This paper aims to investigate the effect of tool path strategies that are contour-in and zigzag tool path strategies applied on tool wear during pocket milling process. The experiments were carried out on CNC vertical machining centre by involving PVD coated carbide inserts. Cutting speed, feed rate and depth of cut were set to vary. In an experiment with three factors at three levels, Response Surface Method (RSM) design of experiment with a standard called Central Composite Design (CCD) was employed. Results obtained indicate that tool wear increases significantly at higher range of feed per tooth compared to cutting speed and depth of cut. This result of this experimental work is then proven statistically by developing empirical model. The prediction model for the response variable of tool wear for contour-in strategy developed in this research shows a good agreement with experimental work.

Application of Elements of TPM Strategy for Operation Analysis of Mining Machine

NASA Astrophysics Data System (ADS)

Brodny, Jaroslaw; Tutak, Magdalena

2017-12-01

Total Productive Maintenance (TPM) strategy includes group of activities and actions in order to maintenance machines in failure-free state and without breakdowns thanks to tending limitation of failures, non-planned shutdowns, lacks and non-planned service of machines. These actions are ordered to increase effectiveness of utilization of possessed devices and machines in company. Very significant element of this strategy is connection of technical actions with changes in their perception by employees. Whereas fundamental aim of introduction this strategy is improvement of economic efficiency of enterprise. Increasing competition and necessity of reduction of production costs causes that also mining enterprises are forced to introduce this strategy. In the paper examples of use of OEE model for quantitative evaluation of selected mining devices were presented. OEE model is quantitative tool of TPM strategy and can be the base for further works connected with its introduction. OEE indicator is the product of three components which include availability and performance of the studied machine and the quality of the obtained product. The paper presents the results of the effectiveness analysis of the use of a set of mining machines included in the longwall system, which is the first and most important link in the technological line of coal production. The set of analyzed machines included the longwall shearer, armored face conveyor and cruscher. From a reliability point of view, the analyzed set of machines is a system that is characterized by the serial structure. The analysis was based on data recorded by the industrial automation system used in the mines. This method of data acquisition ensured their high credibility and a full time synchronization. Conclusions from the research and analyses should be used to reduce breakdowns, failures and unplanned downtime, increase performance and improve production quality.

Machining of Molybdenum by EDM-EP and EDC Processes

NASA Astrophysics Data System (ADS)

Wu, K. L.; Chen, H. J.; Lee, H. M.; Lo, J. S.

2017-12-01

Molybdenum metal (Mo) can be machined with conventional tools and equipment, however, its refractory propertytends to chip when being machined. In this study, the nonconventional processes of electrical discharge machining (EDM) and electro-polishing (EP) have been conducted to investigate the machining of Mo metal and fabrication of Mo grid. Satisfactory surface quality was obtained using appropriate EDM parameters of Ip ≦ 3A and Ton < 80μs at a constant pulse interval of 100μs. The finished Mometal has accomplished by selecting appropriate EP parameters such as electrolyte flow rate of 0.42m/s under EP voltage of 50V and flush time of 20 sec to remove the recast layer and craters on the surface of Mo metal. The surface roughness of machined Mo metal can be improved from Ra of 0.93μm (Rmax = 8.51μm) to 0.23μm (Rmax = 1.48μm). Machined Mo metal surface, when used as grid component in electron gun, needs to be modified by coating materials with high work function, such as silicon carbide (SiC). The main purpose of this study is to explore the electrical discharge coating (EDC) process for coating the SiC layer on EDMed Mo metal. Experimental results proved that the appropriate parameters of Ip = 5A and Ton = 50μs at Toff = 10μs can obtain the deposit with about 60μm thickness. The major phase of deposit on machined Mo surface was SiC ceramic, while the minor phases included MoSi2 and/or SiO2 with the presence of free Si due to improper discharging parameters and the use of silicone oil as the dielectric fluid.

Toolpath strategy for cutter life improvement in plunge milling of AISI H13 tool steel

NASA Astrophysics Data System (ADS)

Adesta, E. Y. T.; Avicenna; hilmy, I.; Daud, M. R. H. C.

2018-01-01

Machinability of AISI H13 tool steel is a prominent issue since the material has the characteristics of high hardenability, excellent wear resistance, and hot toughness. A method of improving cutter life of AISI H13 tool steel plunge milling by alternating the toolpath and cutting conditions is proposed. Taguchi orthogonal array with L9 (3^4) resolution will be employed with one categorical factor of toolpath strategy (TS) and three numeric factors of cutting speed (Vc), radial depth of cut (ae ), and chip load (fz ). It is expected that there are significant differences for each application of toolpath strategy and each cutting condition factor toward the cutting force and tool wear mechanism of the machining process, and medial axis transform toolpath could provide a better tool life improvement by a reduction of cutting force during machining.

Depth indicator and stop aid machining to precise tolerances

NASA Technical Reports Server (NTRS)

Laverty, J. L.

1966-01-01

Attachment for machine tools provides a visual indication of the depth of cut and a positive stop to prevent overcutting. This attachment is used with drill presses, vertical milling machines, and jig borers.

Machine Tool Operation, Course Description.

ERIC Educational Resources Information Center

Denny, Walter E.; Anderson, Floyd L.

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

5 CFR 532.217 - Appropriated fund survey jobs.

Code of Federal Regulations, 2013 CFR

2013-01-01

... agency shall survey the following required jobs: Job title Job grade Janitor (Light) 1 Janitor (Heavy) 2... Equipment Operator 5 Truckdriver (Medium) 6 Truckdriver (Heavy) 7 Machine Tool Operator II 8 Machine Tool Operator I 9 Carpenter 9 Electrician 10 Automotive Mechanic 10 Sheet Metal Mechanic 10 Pipefitter 10 Welder...

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

DOT National Transportation Integrated Search

1982-08-01

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

2. GENERAL VIEW OF HYDRAULIC 48' BORING MILL. Manufactured by ...

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

2. GENERAL VIEW OF HYDRAULIC 48' BORING MILL. Manufactured by Simmons Machine Tool Corporation, Albany, New York, and Betts Company, a division of Niles Tool Company, Hamilton, Ohio. - Juniata Shops, Erecting Shop & Machine Shop, East of Fourth Avenue, between Fourth & Fifth Streets, Altoona, Blair County, PA

Problem Solving and Training Guide for Shipyard Industrial Engineers

DTIC Science & Technology

1986-06-01

Design Integration Tools Building 192 Room 128 9500 MacArthur Blvd Bethesda, MD 20817-5700 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING...called upon to increase the knowledge about industrial engineering of some shipyard group. The Curriculum is seen especially as a tool to identify new...materials on all common machine shop tools . Data permits calculation of machining time. 085 Ostwald, Phillip F. AMERICAN MACHINIST MANUFACTURING COST

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

Clock Agreement Among Parallel Supercomputer Nodes

DOE Data Explorer

Jones, Terry R.; Koenig, Gregory A.

2014-04-30

This dataset presents measurements that quantify the clock synchronization time-agreement characteristics among several high performance computers including the current world's most powerful machine for open science, the U.S. Department of Energy's Titan machine sited at Oak Ridge National Laboratory. These ultra-fast machines derive much of their computational capability from extreme node counts (over 18000 nodes in the case of the Titan machine). Time-agreement is commonly utilized by parallel programming applications and tools, distributed programming application and tools, and system software. Our time-agreement measurements detail the degree of time variance between nodes and how that variance changes over time. The dataset includes empirical measurements and the accompanying spreadsheets.

Machinability of Minor Wooden Species before and after Modification with Thermo-Vacuum Technology

PubMed Central

Sandak, Jakub; Goli, Giacomo; Cetera, Paola; Sandak, Anna; Cavalli, Alberto; Todaro, Luigi

2017-01-01

The influence of the thermal modification process on wood machinability was investigated with four minor species of low economic importance. A set of representative experimental samples was machined to the form of disks with sharp and dull tools. The resulting surface quality was visually evaluated by a team of experts according to the American standard procedure ASTM D-1666-87. The objective quantification of the surface quality was also done by means of a three dimensions (3D) surface scanner for the whole range of grain orientations. Visual assessment and 3D surface analysis showed a good agreement in terms of conclusions. The best quality of the wood surface was obtained when machining thermally modified samples. The positive effect of the material modification was apparent when cutting deodar cedar, black pine and black poplar in unfavorable conditions (i.e., against the grain). The difference was much smaller for an easy-machinability specie such as Italian alder. The use of dull tools resulted in the worst surface quality. Thermal modification has shown a very positive effect when machining with dull tools, leading to a relevant increment of the final surface smoothness. PMID:28772480

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

PubMed

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

2017-09-12

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

Machinability of Minor Wooden Species before and after Modification with Thermo-Vacuum Technology.

PubMed

Sandak, Jakub; Goli, Giacomo; Cetera, Paola; Sandak, Anna; Cavalli, Alberto; Todaro, Luigi

2017-01-28

The influence of the thermal modification process on wood machinability was investigated with four minor species of low economic importance. A set of representative experimental samples was machined to the form of disks with sharp and dull tools. The resulting surface quality was visually evaluated by a team of experts according to the American standard procedure ASTM D-1666-87. The objective quantification of the surface quality was also done by means of a three dimensions (3D) surface scanner for the whole range of grain orientations. Visual assessment and 3D surface analysis showed a good agreement in terms of conclusions. The best quality of the wood surface was obtained when machining thermally modified samples. The positive effect of the material modification was apparent when cutting deodar cedar, black pine and black poplar in unfavorable conditions (i.e., against the grain). The difference was much smaller for an easy-machinability specie such as Italian alder. The use of dull tools resulted in the worst surface quality. Thermal modification has shown a very positive effect when machining with dull tools, leading to a relevant increment of the final surface smoothness.

The Security of Machine Learning

DTIC Science & Technology

2008-04-24

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

Precision lens molding of asphero diffractive surfaces in chalcogenide materials

NASA Astrophysics Data System (ADS)

Nelson, J.; Scordato, M.; Schwertz, K.; Bagwell, J.

2015-10-01

Finished lens molding, and the similar process of precision lens molding, have long been practiced for high volume, accurate replication of optical surfaces on oxide glass. The physics surrounding these processes are well understood, and the processes are capable of producing high quality optics with great fidelity. However, several limitations exist due to properties inherent with oxide glasses. Tooling materials that can withstand the severe environmental conditions of oxide glass molding cannot easily be machined to produce complex geometries such as diffractive surfaces, lens arrays, and off axis features. Current machining technologies coupled with a limited selection of tool materials greatly limits the type of structures that can be molded into the finished optic. Tooling for chalcogenide glasses are not bound by these restrictions since the molding temperatures required are much lower than for oxide glasses. Innovations in tooling materials and manufacturing techniques have enabled the production of complex geometries to optical quality specifications and have demonstrated the viability of creating tools for molding diffractive surfaces, off axis features, datums, and arrays. Applications for optics having these features are found in automotive, defense, security, medical, and industrial domains. This paper will discuss results achieved in the study of various molding techniques for the formation of positive diffractive features on a concave spherical surface molded from As2Se3 chalcogenide glass. Examples and results of molding with tools having CTE match with the glass and non CTE match will be reviewed. The formation of stress within the glass during molding will be discussed, and methods of stress management will also be demonstrated and discussed. Results of process development methods and production of good diffractive surfaces will be shown.

Working with the superabrasives industry to optimize tooling for grinding brittle materials

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

Taylor, J.S.; Piscotty, M.A.; Blaedel, K.L.

1996-05-01

The optics manufacturing industry is undertaking a significant modernization, as computer-numeric-controlled (CNC) equipment is joining or replacing open-loop equipment and hand lapping/polishing on the shop floor. Several prototype CNC lens grinding platforms employing ring tools are undergoing development and demonstration at the Center for Optics Manufacturing in Rochester, NY, and several machine tool companies have CNC product lines aimed at the optics industry. Benefits to using CNC ring tool grinding equipment include: essentially unlimited flexibility in selecting radii of curvature without special radiused tooling, the potential for CIM linkages to CAD workstations, and the cultural shift from craftsmen with undocumentedmore » procedures to CNC machine operators employing computerized routines for process control. In recent years, these developments, have inspired a number of US optics companies to invest in CNC equipment and participate in process development activities involving bound diamond tooling. This modernization process,extends beyond large optics companies that have historically embraced advanced equipment, to also include smaller optical shops where a shift to CNC equipment requires a significant company commitment. This paper addresses our efforts to optimize fine grinding wheels to support the new generation of CNC equipment. We begin with a discussion of how fine grinding fits into the optical production process, and then describe an initiative for improving the linkage between optics industry and the grinding wheel industry. For the purposes of this paper, we define fine wheels to have diamond sizes below 20 micrometers, which includes wheels used for what is sometimes called medium grinding (e.g. 10-20 micrometers diamond) and for fine grinding (e.g. 2-4 micrometers diamond).« less

Critical Technology Assessment of Five Axis Simultaneous Control Machine Tools

DTIC Science & Technology

2009-07-01

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

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.

Wear of Cutting Tool with Excel Geometry in Turning Process of Hardened Steel

NASA Astrophysics Data System (ADS)

Samardžiová, Michaela

2016-09-01

This paper deals with hard turning using a cutting tool with Xcel geometry. This is one of the new geometries, and there is not any information about Xcel wear in comparison to the conventional geometry. It is already known from cutting tools producers that using the Xcel geometry leads to higher quality of machined surface, perticularly surface roughness. It is possible to achieve more than 4 times lower Ra and Rz values after turning than after using conventional geometry with radius. The workpiece material was 100Cr6 hardened steel with hardness of 60 ± 1 HRC. The machine used for the experiment was a lathe with counter spindle DMG CTX alpha 500, which is located in the Centre of Excellence of 5-axis Machining at the Faculty of Materials Science and Technology in Trnava. The cutting tools made by CBN were obtained from Sandvik COROMANT Company. The aim of this paper is to investigate the cutting tool wear in hard turning process by the Xcel cutting tool geometry.

Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.

PubMed

Romeo, Valeria; Maurea, Simone; Cuocolo, Renato; Petretta, Mario; Mainenti, Pier Paolo; Verde, Francesco; Coppola, Milena; Dell'Aversana, Serena; Brunetti, Arturo

2018-01-17

Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal lesions (NAL) may be challenging. Texture analysis (TA) can extract quantitative parameters from MR images. Machine learning is a technique for recognizing patterns that can be applied to medical images by identifying the best combination of TA features to create a predictive model for the diagnosis of interest. To assess the diagnostic efficacy of TA-derived parameters extracted from MR images in characterizing LRA, LPA, and NAL using a machine-learning approach. Retrospective, observational study. Sixty MR examinations, including 20 LRA, 20 LPA, and 20 NAL. Unenhanced T 1 -weighted in-phase (IP) and out-of-phase (OP) as well as T 2 -weighted (T 2 -w) MR images acquired at 3T. Adrenal lesions were manually segmented, placing a spherical volume of interest on IP, OP, and T 2 -w images. Different selection methods were trained and tested using the J48 machine-learning classifiers. The feature selection method that obtained the highest diagnostic performance using the J48 classifier was identified; the diagnostic performance was also compared with that of a senior radiologist by means of McNemar's test. A total of 138 TA-derived features were extracted; among these, four features were selected, extracted from the IP (Short_Run_High_Gray_Level_Emphasis), OP (Mean_Intensity and Maximum_3D_Diameter), and T 2 -w (Standard_Deviation) images; the J48 classifier obtained a diagnostic accuracy of 80%. The expert radiologist obtained a diagnostic accuracy of 73%. McNemar's test did not show significant differences in terms of diagnostic performance between the J48 classifier and the expert radiologist. Machine learning conducted on MR TA-derived features is a potential tool to characterize adrenal lesions. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Collaborative business process support in eHealth: integrating IHE profiles through ebXML business process specification language.

PubMed

Dogac, Asuman; Kabak, Yildiray; Namli, Tuncay; Okcan, Alper

2008-11-01

Integrating healthcare enterprise (IHE) specifies integration profiles describing selected real world use cases to facilitate the interoperability of healthcare information resources. While realizing a complex real-world scenario, IHE profiles are combined by grouping the related IHE actors. Grouping IHE actors implies that the associated business processes (IHE profiles) that the actors are involved must be combined, that is, the choreography of the resulting collaborative business process must be determined by deciding on the execution sequence of transactions coming from different profiles. There are many IHE profiles and each user or vendor may support a different set of IHE profiles that fits to its business need. However, determining the precedence of all the involved transactions manually for each possible combination of the profiles is a very tedious task. In this paper, we describe how to obtain the overall business process automatically when IHE actors are grouped. For this purpose, we represent the IHE profiles through a standard, machine-processable language, namely, Organization for the Advancement of Structured Information Standards (OASIS) ebusiness eXtensible Markup Language (ebXML) Business Process Specification (ebBP) Language. We define the precedence rules among the transactions of the IHE profiles, again, in a machine-processable way. Then, through a graphical tool, we allow users to select the actors to be grouped and automatically produce the overall business process in a machine-processable format.

Angular approach combined to mechanical model for tool breakage detection by eddy current sensors

NASA Astrophysics Data System (ADS)

Ritou, M.; Garnier, S.; Furet, B.; Hascoet, J. Y.

2014-02-01

The paper presents a new complete approach for Tool Condition Monitoring (TCM) in milling. The aim is the early detection of small damages so that catastrophic tool failures are prevented. A versatile in-process monitoring system is introduced for reliability concerns. The tool condition is determined by estimates of the radial eccentricity of the teeth. An adequate criterion is proposed combining mechanical model of milling and angular approach.Then, a new solution is proposed for the estimate of cutting force using eddy current sensors implemented close to spindle nose. Signals are analysed in the angular domain, notably by synchronous averaging technique. Phase shifts induced by changes of machining direction are compensated. Results are compared with cutting forces measured with a dynamometer table.The proposed method is implemented in an industrial case of pocket machining operation. One of the cutting edges has been slightly damaged during the machining, as shown by a direct measurement of the tool. A control chart is established with the estimates of cutter eccentricity obtained during the machining from the eddy current sensors signals. Efficiency and reliability of the method is demonstrated by a successful detection of the damage.

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.

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.

Fast detection of peroxidase (POD) activity in tomato leaves which infected with Botrytis cinerea using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Kong, Wenwen; Liu, Fei; Zhang, Chu; Bao, Yidan; Yu, Jiajia; He, Yong

2014-01-01

Tomatoes are cultivated around the world and gray mold is one of its most prominent and destructive diseases. An early disease detection method can decrease losses caused by plant diseases and prevent the spread of diseases. The activity of peroxidase (POD) is very important indicator of disease stress for plants. The objective of this study is to examine the possibility of fast detection of POD activity in tomato leaves which infected with Botrytis cinerea using hyperspectral imaging data. Five pre-treatment methods were investigated. Genetic algorithm-partial least squares (GA-PLS) was applied to select optimal wavelengths. A new fast learning neural algorithm named extreme learning machine (ELM) was employed as multivariate analytical tool in this study. 21 optimal wavelengths were selected by GA-PLS and used as inputs of three calibration models. The optimal prediction result was achieved by ELM model with selected wavelengths, and the r and RMSEP in validation were 0.8647 and 465.9880 respectively. The results indicated that hyperspectral imaging could be considered as a valuable tool for POD activity prediction. The selected wavelengths could be potential resources for instrument development.

Cold machining of high density tungsten and other materials

NASA Technical Reports Server (NTRS)

Ziegelmeier, P.

1969-01-01

Cold machining process, which uses a sub-zero refrigerated cutting fluid, is used for machining refractory or reactive metals and alloys. Special carbide tools for turning and drilling these alloys further improve the cutting performance.

Optimization of cutting parameters in CNC turning of stainless steel 304 with TiAlN nano coated carbide cutting tool

NASA Astrophysics Data System (ADS)

Durga Prasada Rao, V.; Harsha, N.; Raghu Ram, N. S.; Navya Geethika, V.

2018-02-01

In this work, turning was performed to optimize the surface finish or roughness (Ra) of stainless steel 304 with uncoated and coated carbide tools under dry conditions. The carbide tools were coated with Titanium Aluminium Nitride (TiAlN) nano coating using Physical Vapour Deposition (PVD) method. The machining parameters, viz., cutting speed, depth of cut and feed rate which show major impact on Ra are considered during turning. The experiments are designed as per Taguchi orthogonal array and machining process is done accordingly. Then second-order regression equations have been developed on the basis of experimental results for Ra in terms of machining parameters used. Regarding the effect of machining parameters, an upward trend is observed in Ra with respect to feed rate, and as cutting speed increases the Ra value increased slightly due to chatter and vibrations. The adequacy of response variable (Ra) is tested by conducting additional experiments. The predicted Ra values are found to be a close match of their corresponding experimental values of uncoated and coated tools. The corresponding average % errors are found to be within the acceptable limits. Then the surface roughness equations of uncoated and coated tools are set as the objectives of optimization problem and are solved by using Differential Evolution (DE) algorithm. Also the tool lives of uncoated and coated tools are predicted by using Taylor’s tool life equation.

Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.

PubMed

Das, Koel; Giesbrecht, Barry; Eckstein, Miguel P

2010-07-15

Within the past decade computational approaches adopted from the field of machine learning have provided neuroscientists with powerful new tools for analyzing neural data. For instance, previous studies have applied pattern classification algorithms to electroencephalography data to predict the category of presented visual stimuli, human observer decision choices and task difficulty. Here, we quantitatively compare the ability of pattern classifiers and three ERP metrics (peak amplitude, mean amplitude, and onset latency of the face-selective N170) to predict variations across individuals' behavioral performance in a difficult perceptual task identifying images of faces and cars embedded in noise. We investigate three different pattern classifiers (Classwise Principal Component Analysis, CPCA; Linear Discriminant Analysis, LDA; and Support Vector Machine, SVM), five training methods differing in the selection of training data sets and three analyses procedures for the ERP measures. We show that all three pattern classifier algorithms surpass traditional ERP measurements in their ability to predict individual differences in performance. Although the differences across pattern classifiers were not large, the CPCA method with training data sets restricted to EEG activity for trials in which observers expressed high confidence about their decisions performed the highest at predicting perceptual performance of observers. We also show that the neural activity predicting the performance across individuals was distributed through time starting at 120ms, and unlike the face-selective ERP response, sustained for more than 400ms after stimulus presentation, indicating that both early and late components contain information correlated with observers' behavioral performance. Together, our results further demonstrate the potential of pattern classifiers compared to more traditional ERP techniques as an analysis tool for modeling spatiotemporal dynamics of the human brain and relating neural activity to behavior. Copyright 2010 Elsevier Inc. All rights reserved.

An Analysis of the Effects of Chip-groove Geometry on Machining Performance Using Finite Element Methods

NASA Astrophysics Data System (ADS)

Ee, K. C.; Dillon, O. W.; Jawahir, I. S.

2004-06-01

This paper discusses the influence of major chip-groove parameters of a cutting tool on the chip formation process in orthogonal machining using finite element (FE) methods. In the FE formulation, a thermal elastic-viscoplastic material model is used together with a modified Johnson-Cook material law for the flow stress. The chip back-flow angle and the chip up-curl radius are calculated for a range of cutting conditions by varying the chip-groove parameters. The analysis provides greater understanding of the effectiveness of chip-groove configurations and points a way to correlate cutting conditions with tool-wear when machining with a grooved cutting tool.

Producing Production Level Tooling in Prototype Timing

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

Mc Hugh, Kevin Matthew; Knirsch, J.

A new rapid solidification process machine will be able to produce eight-inch diameter by six-inch thick finished cavities at the rate of one per hour - a rate that will change the tooling industry dramatically. Global Metal Technologies, Inc. (GMTI) (Solon, OH) has signed an exclusive license with Idaho National Engineered and Environmental Laboratories (INEEL) (Idaho Falls, ID) for the development and commercialization of the rapid solidification process (RSP tooling). The first production machine is scheduled for delivery in July 2001. The RSP tooling process is a method of producing production level tooling in prototype timing. The process' inventor, Kevinmore » McHugh, describes it as a rapid solidification method, which differentiates it from the standard spray forming methods. RSP itself is relatively straightforward. Molten metal is sprayed against the ceramic pattern, replicating the pattern's contours, surface texture and details. After spraying, the molten tool steel is cooled at room temperature and separated from the pattern. The irregular periphery of the freshly sprayed insert is squared off, either by machining or, in the case of harder tool steels, by wire EDM. XX« less

Cutting tool form compensation system and method

DOEpatents

Barkman, W.E.; Babelay, E.F. Jr.; Klages, E.J.

1993-10-19

A compensation system for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along a preprogrammed path during a machining operation utilizes a camera and a vision computer for gathering information at a preselected stage of a machining operation relating to the actual shape and size of the cutting edge of the cutting tool and for altering the preprogrammed path in accordance with detected variations between the actual size and shape of the cutting edge and an assumed size and shape of the cutting edge. The camera obtains an image of the cutting tool against a background so that the cutting tool and background possess contrasting light intensities, and the vision computer utilizes the contrasting light intensities of the image to locate points therein which correspond to points along the actual cutting edge. Following a series of computations involving the determining of a tool center from the points identified along the tool edge, the results of the computations are fed to the controller where the preprogrammed path is altered as aforedescribed. 9 figures.

Cutting tool form compensaton system and method

DOEpatents

Barkman, William E.; Babelay, Jr., Edwin F.; Klages, Edward J.

1993-01-01

A compensation system for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along a preprogrammed path during a machining operation utilizes a camera and a vision computer for gathering information at a preselected stage of a machining operation relating to the actual shape and size of the cutting edge of the cutting tool and for altering the preprogrammed path in accordance with detected variations between the actual size and shape of the cutting edge and an assumed size and shape of the cutting edge. The camera obtains an image of the cutting tool against a background so that the cutting tool and background possess contrasting light intensities, and the vision computer utilizes the contrasting light intensities of the image to locate points therein which correspond to points along the actual cutting edge. Following a series of computations involving the determining of a tool center from the points identified along the tool edge, the results of the computations are fed to the controller where the preprogrammed path is altered as aforedescribed.

Applying CBR to machine tool product configuration design oriented to customer requirements

NASA Astrophysics Data System (ADS)

Wang, Pengjia; Gong, Yadong; Xie, Hualong; Liu, Yongxian; Nee, Andrew Yehching

2017-01-01

Product customization is a trend in the current market-oriented manufacturing environment. However, deduction from customer requirements to design results and evaluation of design alternatives are still heavily reliant on the designer's experience and knowledge. To solve the problem of fuzziness and uncertainty of customer requirements in product configuration, an analysis method based on the grey rough model is presented. The customer requirements can be converted into technical characteristics effectively. In addition, an optimization decision model for product planning is established to help the enterprises select the key technical characteristics under the constraints of cost and time to serve the customer to maximal satisfaction. A new case retrieval approach that combines the self-organizing map and fuzzy similarity priority ratio method is proposed in case-based design. The self-organizing map can reduce the retrieval range and increase the retrieval efficiency, and the fuzzy similarity priority ratio method can evaluate the similarity of cases comprehensively. To ensure that the final case has the best overall performance, an evaluation method of similar cases based on grey correlation analysis is proposed to evaluate similar cases to select the most suitable case. Furthermore, a computer-aided system is developed using MATLAB GUI to assist the product configuration design. The actual example and result on an ETC series machine tool product show that the proposed method is effective, rapid and accurate in the process of product configuration. The proposed methodology provides a detailed instruction for the product configuration design oriented to customer requirements.

Looking west at Machine Shop (Bldg. 163) south bay interior. ...

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

Looking west at Machine Shop (Bldg. 163) south bay interior. Note the Shaw 15-ton bridge crane. This portion of the building housed machine tools and locomotive component repair functions that supported the erecting shop operations - Atchison, Topeka, Santa Fe Railroad, Albuquerque Shops, Machine Shop, 908 Second Street, Southwest, Albuquerque, Bernalillo County, NM

Characteristics for electrochemical machining with nanoscale voltage pulses.

PubMed

Lee, E S; Back, S Y; Lee, J T

2009-06-01

Electrochemical machining has traditionally been used in highly specialized fields, such as those of the aerospace and defense industries. It is now increasingly being applied in other industries, where parts with difficult-to-cut material, complex geometry and tribology, and devices of nanoscale and microscale are required. Electric characteristic plays a principal function role in and chemical characteristic plays an assistant function role in electrochemical machining. Therefore, essential parameters in electrochemical machining can be described current density, machining time, inter-electrode gap size, electrolyte, electrode shape etc. Electrochemical machining provides an economical and effective method for machining high strength, high tension and heat-resistant materials into complex shapes such as turbine blades of titanium and aluminum alloys. The application of nanoscale voltage pulses between a tool electrode and a workpiece in an electrochemical environment allows the three-dimensional machining of conducting materials with sub-micrometer precision. In this study, micro probe are developed by electrochemical etching and micro holes are manufactured using these micro probe as tool electrodes. Micro holes and microgroove can be accurately achieved by using nanoscale voltages pulses.

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

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

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

2015-08-01

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

Rapid Prototyping: State of the Art Review

DTIC Science & Technology

2003-10-23

Steel H13 Tool Steel CP Ti, Ti-6Al-4V Titanium Tungsten Copper Aluminum Nickel...The company’s LENS 750 and LENS 850 machines (both $440,000 to $640,000) are capable of producing parts in 16 stainless steel , H13 tool steel ...machining. 20 The Arcam EBM S12 model sells for $500,000 and is capable of processing two materials. One is H13 tool steel , while the other

Toward Intelligent Machine Learning Algorithms

DTIC Science & Technology

1988-05-01

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

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.

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.

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

Mathematical model of simple spalling formation during coal cutting with extracting machine

NASA Astrophysics Data System (ADS)

Gabov, V. V.; Zadkov, D. A.

2018-05-01

A single-mass model of a rotor shearer is analyzed. It is shown that rotor mining machines has large inertia moments and load dynamics. An extraction module model with selective movement of the cutting tool is represented. The peculiar feature of such extracting machines is fluid power drive cutter mechanism. They can steadily operate at large shear thickness, and locking modes are not an emergency for them. Comparing with shearers they have less inertional mass, but slower average cutting speed, and its momentary values depend on load. Basing on the equation of hydraulic fuel consumption balance the work of fluid power drive of extracting module cutter mechanism together with hydro pneumatic accumulator is analyzed. Spalling formation model during coal cutting with fluid power drive cutter mechanism and potential energy stores are suggested. Matching cutter speed with the speed of main crack expansion and amount of potential energy consumption, cutter load is determined only by ultimate stress at crack pole and friction. Tests of an extracting module cutter in real size model proved the stated theory.

Localization of thermal anomalies in electrical equipment using Infrared Thermography and support vector machine

NASA Astrophysics Data System (ADS)

Laib dit Leksir, Y.; Mansour, M.; Moussaoui, A.

2018-03-01

Analysis and processing of databases obtained from infrared thermal inspections made on electrical installations require the development of new tools to obtain more information to visual inspections. Consequently, methods based on the capture of thermal images show a great potential and are increasingly employed in this field. However, there is a need for the development of effective techniques to analyse these databases in order to extract significant information relating to the state of the infrastructures. This paper presents a technique explaining how this approach can be implemented and proposes a system that can help to detect faults in thermal images of electrical installations. The proposed method classifies and identifies the region of interest (ROI). The identification is conducted using support vector machine (SVM) algorithm. The aim here is to capture the faults that exist in electrical equipments during an inspection of some machines using A40 FLIR camera. After that, binarization techniques are employed to select the region of interest. Later the comparative analysis of the obtained misclassification errors using the proposed method with Fuzzy c means and Ostu, has also be addressed.

75 FR 3253 - Lamb Assembly and Test, LLC, Subsidiary of Mag Industrial Automation Systems, Machesney Park, IL...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-20

..., LLC, Subsidiary of Mag Industrial Automation Systems, Machesney Park, IL; Notice of Negative... automation equipment and machine tools did not contribute to worker separations at the subject facility and...' firm's declining customers. The survey revealed no imports of automation equipment and machine tools by...

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

ERIC Educational Resources Information Center

RONEY, MAURICE W.; AND OTHERS

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

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.

Step-and-Repeat Nanoimprint-, Photo- and Laser Lithography from One Customised CNC Machine.

PubMed

Greer, Andrew Im; Della-Rosa, Benoit; Khokhar, Ali Z; Gadegaard, Nikolaj

2016-12-01

The conversion of a computer numerical control machine into a nanoimprint step-and-repeat tool with additional laser- and photolithography capacity is documented here. All three processes, each demonstrated on a variety of photoresists, are performed successfully and analysed so as to enable the reader to relate their known lithography process(es) to the findings. Using the converted tool, 1 cm(2) of nanopattern may be exposed in 6 s, over 3300 times faster than the electron beam equivalent. Nanoimprint tools are commercially available, but these can cost around 1000 times more than this customised computer numerical control (CNC) machine. The converted equipment facilitates rapid production and large area micro- and nanoscale research on small grants, ultimately enabling faster and more diverse growth in this field of science. In comparison to commercial tools, this converted CNC also boasts capacity to handle larger substrates, temperature control and active force control, up to ten times more curing dose and compactness. Actual devices are fabricated using the machine including an expanded nanotopographic array and microfluidic PDMS Y-channel mixers.

Step-and-Repeat Nanoimprint-, Photo- and Laser Lithography from One Customised CNC Machine

NASA Astrophysics Data System (ADS)

Greer, Andrew IM; Della-Rosa, Benoit; Khokhar, Ali Z.; Gadegaard, Nikolaj

2016-03-01

The conversion of a computer numerical control machine into a nanoimprint step-and-repeat tool with additional laser- and photolithography capacity is documented here. All three processes, each demonstrated on a variety of photoresists, are performed successfully and analysed so as to enable the reader to relate their known lithography process(es) to the findings. Using the converted tool, 1 cm2 of nanopattern may be exposed in 6 s, over 3300 times faster than the electron beam equivalent. Nanoimprint tools are commercially available, but these can cost around 1000 times more than this customised computer numerical control (CNC) machine. The converted equipment facilitates rapid production and large area micro- and nanoscale research on small grants, ultimately enabling faster and more diverse growth in this field of science. In comparison to commercial tools, this converted CNC also boasts capacity to handle larger substrates, temperature control and active force control, up to ten times more curing dose and compactness. Actual devices are fabricated using the machine including an expanded nanotopographic array and microfluidic PDMS Y-channel mixers.

High productivity machining of holes in Inconel 718 with SiAlON tools

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Tribology in secondary wood machining

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

Ko, P.L.; Hawthorne, H.M.; Andiappan, J.

Secondary wood manufacturing covers a wide range of products from furniture, cabinets, doors and windows, to musical instruments. Many of these are now mass produced in sophisticated, high speed numerical controlled machines. The performance and the reliability of the tools are key to an efficient and economical manufacturing process as well as to the quality of the finished products. A program concerned with three aspects of tribology of wood machining, namely, tool wear, tool-wood friction characteristics and wood surface quality characterization, was set up in the Integrated Manufacturing Technologies Institute (IMTI) of the National Research Council of Canada. The studiesmore » include friction and wear mechanism identification and modeling, wear performance of surface-engineered tool materials, friction-induced vibration and cutting efficiency, and the influence of wear and friction on finished products. This research program underlines the importance of tribology in secondary wood manufacturing and at the same time adds new challenges to tribology research since wood is a complex, heterogeneous, material and its behavior during machining is highly sensitive to the surrounding environments and to the moisture content in the work piece.« less

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

NASA Astrophysics Data System (ADS)

Ahrstrom, Jeffrey D.

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

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.

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

NASA Astrophysics Data System (ADS)

Liu, Guanglei; Chang, Kai; Liu, Zeliang

2013-05-01

Although a great deal of research has been dedicated to the synthesis of spiral bevel gears, little related to reverse engineering can be found. An approach is proposed to reverse the machine-tool settings of the pinion of a spiral bevel gear drive on the basis of the blank and tooth surface data obtained by a coordinate measuring machine(CMM). Real tooth contact analysis(RTCA) is performed to preliminary ascertain the contact pattern, the motion curve, as well as the position of the mean contact point. And then the tangent to the contact path and the motion curve are interpolated in the sense of the least square method to extract the initial values of the bias angle and the higher order coefficients(HOC) in modified roll motion. A trial tooth surface is generated by machine-tool settings derived from the local synthesis relating to the initial meshing performances and modified roll motion. An optimization objective is formed which equals the tooth surface deviation between the real tooth surface and the trial tooth surface. The design variables are the parameters describing the meshing performances at the mean contact point in addition to the HOC. When the objective is optimized within an arbitrarily given convergence tolerance, the machine-tool settings together with the HOC are obtained. The proposed approach is verified by a spiral bevel pinion used in the accessory gear box of an aviation engine. The trial tooth surfaces approach to the real tooth surface on the whole in the example. The results show that the convergent tooth surface deviation for the concave side on the average is less than 0.5 μm, and is less than 1.3 μm for the convex side. The biggest tooth surface deviation is 6.7 μm which is located at the corner of the grid on the convex side. Those nodes with relative bigger tooth surface deviations are all located at the boundary of the grid. An approach is proposed to figure out the machine-tool settings of a spiral bevel pinion by way of reverse engineering without having known the theoretical tooth surfaces and the corresponding machine-tool settings.

OrthoSelect: a protocol for selecting orthologous groups in phylogenomics.

PubMed

Schreiber, Fabian; Pick, Kerstin; Erpenbeck, Dirk; Wörheide, Gert; Morgenstern, Burkhard

2009-07-16

Phylogenetic studies using expressed sequence tags (EST) are becoming a standard approach to answer evolutionary questions. Such studies are usually based on large sets of newly generated, unannotated, and error-prone EST sequences from different species. A first crucial step in EST-based phylogeny reconstruction is to identify groups of orthologous sequences. From these data sets, appropriate target genes are selected, and redundant sequences are eliminated to obtain suitable sequence sets as input data for tree-reconstruction software. Generating such data sets manually can be very time consuming. Thus, software tools are needed that carry out these steps automatically. We developed a flexible and user-friendly software pipeline, running on desktop machines or computer clusters, that constructs data sets for phylogenomic analyses. It automatically searches assembled EST sequences against databases of orthologous groups (OG), assigns ESTs to these predefined OGs, translates the sequences into proteins, eliminates redundant sequences assigned to the same OG, creates multiple sequence alignments of identified orthologous sequences and offers the possibility to further process this alignment in a last step by excluding potentially homoplastic sites and selecting sufficiently conserved parts. Our software pipeline can be used as it is, but it can also be adapted by integrating additional external programs. This makes the pipeline useful for non-bioinformaticians as well as to bioinformatic experts. The software pipeline is especially designed for ESTs, but it can also handle protein sequences. OrthoSelect is a tool that produces orthologous gene alignments from assembled ESTs. Our tests show that OrthoSelect detects orthologs in EST libraries with high accuracy. In the absence of a gold standard for orthology prediction, we compared predictions by OrthoSelect to a manually created and published phylogenomic data set. Our tool was not only able to rebuild the data set with a specificity of 98%, but it detected four percent more orthologous sequences. Furthermore, the results OrthoSelect produces are in absolut agreement with the results of other programs, but our tool offers a significant speedup and additional functionality, e.g. handling of ESTs, computing sequence alignments, and refining them. To our knowledge, there is currently no fully automated and freely available tool for this purpose. Thus, OrthoSelect is a valuable tool for researchers in the field of phylogenomics who deal with large quantities of EST sequences. OrthoSelect is written in Perl and runs on Linux/Mac OS X. The tool can be downloaded at (http://gobics.de/fabian/orthoselect.php).

An experimental investigation of pulsed laser-assisted machining of AISI 52100 steel

NASA Astrophysics Data System (ADS)

Panjehpour, Afshin; Soleymani Yazdi, Mohammad R.; Shoja-Razavi, Reza

2014-11-01

Grinding and hard turning are widely used for machining of hardened bearing steel parts. Laser-assisted machining (LAM) has emerged as an efficient alternative to grinding and hard turning for hardened steel parts. In most cases, continuous-wave lasers were used as a heat source to cause localized heating prior to material removal by a cutting tool. In this study, an experimental investigation of pulsed laser-assisted machining of AISI 52100 bearing steel was conducted. The effects of process parameters (i.e., laser mean power, pulse frequency, pulse energy, cutting speed and feed rate) on state variables (i.e., material removal temperature, specific cutting energy, surface roughness, microstructure, tool wear and chip formation) were investigated. At laser mean power of 425 W with frequency of 120 Hz and cutting speed of 70 m/min, the benefit of LAM was shown by 25% decrease in specific cutting energy and 18% improvement in surface roughness, as compared to those of the conventional machining. It was shown that at constant laser power, the increase of laser pulse energy causes the rapid increase in tool wear rate. Pulsed laser allowed efficient control of surface temperature and heat penetration in material removal region. Examination of the machined subsurface microstructure and microhardness profiles showed no change under LAM and conventional machining. Continuous chips with more uniform plastic deformation were produced in LAM.

Modelling and simulation of effect of ultrasonic vibrations on machining of Ti6Al4V.

PubMed

Patil, Sandip; Joshi, Shashikant; Tewari, Asim; Joshi, Suhas S

2014-02-01

The titanium alloys cause high machining heat generation and consequent rapid wear of cutting tool edges during machining. The ultrasonic assisted turning (UAT) has been found to be very effective in machining of various materials; especially in the machining of "difficult-to-cut" material like Ti6Al4V. The present work is a comprehensive study involving 2D FE transient simulation of UAT in DEFORM framework and their experimental characterization. The simulation shows that UAT reduces the stress level on cutting tool during machining as compared to that of in continuous turning (CT) barring the penetration stage, wherein both tools are subjected to identical stress levels. There is a 40-45% reduction in cutting forces and about 48% reduction in cutting temperature in UAT over that of in CT. However, the reduction magnitude reduces with an increase in the cutting speed. The experimental analysis of UAT process shows that the surface roughness in UAT is lower than in CT, and the UATed surfaces have matte finish as against the glossy finish on the CTed surfaces. Microstructural observations of the chips and machined surfaces in both processes reveal that the intensity of thermal softening and shear band formation is reduced in UAT over that of in CT. Copyright © 2013 Elsevier B.V. All rights reserved.

Hybrid micromachining using a nanosecond pulsed laser and micro EDM

NASA Astrophysics Data System (ADS)

Kim, Sanha; Kim, Bo Hyun; Chung, Do Kwan; Shin, Hong Shik; Chu, Chong Nam

2010-01-01

Micro electrical discharge machining (micro EDM) is a well-known precise machining process that achieves micro structures of excellent quality for any conductive material. However, the slow machining speed and high tool wear are main drawbacks of this process. Though the use of deionized water instead of kerosene as a dielectric fluid can reduce the tool wear and increase the machine speed, the material removal rate (MRR) is still low. In contrast, laser ablation using a nanosecond pulsed laser is a fast and non-wear machining process but achieves micro figures of rather low quality. Therefore, the integration of these two processes can overcome the respective disadvantages. This paper reports a hybrid process of a nanosecond pulsed laser and micro EDM for micromachining. A novel hybrid micromachining system that combines the two discrete machining processes is introduced. Then, the feasibility and characteristics of the hybrid machining process are investigated compared to conventional EDM and laser ablation. It is verified experimentally that the machining time can be effectively reduced in both EDM drilling and milling by rapid laser pre-machining prior to micro EDM. Finally, some examples of complicated 3D micro structures fabricated by the hybrid process are shown.

Improving human activity recognition and its application in early stroke diagnosis.

PubMed

Villar, José R; González, Silvia; Sedano, Javier; Chira, Camelia; Trejo-Gabriel-Galan, Jose M

2015-06-01

The development of efficient stroke-detection methods is of significant importance in today's society due to the effects and impact of stroke on health and economy worldwide. This study focuses on Human Activity Recognition (HAR), which is a key component in developing an early stroke-diagnosis tool. An overview of the proposed global approach able to discriminate normal resting from stroke-related paralysis is detailed. The main contributions include an extension of the Genetic Fuzzy Finite State Machine (GFFSM) method and a new hybrid feature selection (FS) algorithm involving Principal Component Analysis (PCA) and a voting scheme putting the cross-validation results together. Experimental results show that the proposed approach is a well-performing HAR tool that can be successfully embedded in devices.

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

Belley, M; Schmidt, M; Knutson, N

Purpose: Physics second-checks for external beam radiation therapy are performed, in-part, to verify that the machine parameters in the Record-and-Verify (R&V) system that will ultimately be sent to the LINAC exactly match the values initially calculated by the Treatment Planning System (TPS). While performing the second-check, a large portion of the physicists’ time is spent navigating and arranging display windows to locate and compare the relevant numerical values (MLC position, collimator rotation, field size, MU, etc.). Here, we describe the development of a software tool that guides the physicist by aggregating and succinctly displaying machine parameter data relevant to themore » physics second-check process. Methods: A data retrieval software tool was developed using Python to aggregate data and generate a list of machine parameters that are commonly verified during the physics second-check process. This software tool imported values from (i) the TPS RT Plan DICOM file and (ii) the MOSAIQ (R&V) Structured Query Language (SQL) database. The machine parameters aggregated for this study included: MLC positions, X&Y jaw positions, collimator rotation, gantry rotation, MU, dose rate, wedges and accessories, cumulative dose, energy, machine name, couch angle, and more. Results: A GUI interface was developed to generate a side-by-side display of the aggregated machine parameter values for each field, and presented to the physicist for direct visual comparison. This software tool was tested for 3D conformal, static IMRT, sliding window IMRT, and VMAT treatment plans. Conclusion: This software tool facilitated the data collection process needed in order for the physicist to conduct a second-check, thus yielding an optimized second-check workflow that was both more user friendly and time-efficient. Utilizing this software tool, the physicist was able to spend less time searching through the TPS PDF plan document and the R&V system and focus the second-check efforts on assessing the patient-specific plan-quality.« less

MicroRNA based Pan-Cancer Diagnosis and Treatment Recommendation.

PubMed

Cheerla, Nikhil; Gevaert, Olivier

2017-01-13

The current state-of-the-art in cancer diagnosis and treatment is not ideal; diagnostic tests are accurate but invasive, and treatments are "one-size fits-all" instead of being personalized. Recently, miRNA's have garnered significant attention as cancer biomarkers, owing to their ease of access (circulating miRNA in the blood) and stability. There have been many studies showing the effectiveness of miRNA data in diagnosing specific cancer types, but few studies explore the role of miRNA in predicting treatment outcome. Here we go a step further, using tissue miRNA and clinical data across 21 cancers from the 'The Cancer Genome Atlas' (TCGA) database. We use machine learning techniques to create an accurate pan-cancer diagnosis system, and a prediction model for treatment outcomes. Finally, using these models, we create a web-based tool that diagnoses cancer and recommends the best treatment options. We achieved 97.2% accuracy for classification using a support vector machine classifier with radial basis. The accuracies improved to 99.9-100% when climbing up the embryonic tree and classifying cancers at different stages. We define the accuracy as the ratio of the total number of instances correctly classified to the total instances. The classifier also performed well, achieving greater than 80% sensitivity for many cancer types on independent validation datasets. Many miRNAs selected by our feature selection algorithm had strong previous associations to various cancers and tumor progression. Then, using miRNA, clinical and treatment data and encoding it in a machine-learning readable format, we built a prognosis predictor model to predict the outcome of treatment with 85% accuracy. We used this model to create a tool that recommends personalized treatment regimens. Both the diagnosis and prognosis model, incorporating semi-supervised learning techniques to improve their accuracies with repeated use, were uploaded online for easy access. Our research is a step towards the final goal of diagnosing cancer and predicting treatment recommendations using non-invasive blood tests.

13. Interior detail, Blacksmith Shop, showing a portion of the ...

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

13. Interior detail, Blacksmith Shop, showing a portion of the original overhead belt drive system that powered machine tools in the adjacent Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to west, 135mm lens. - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

Table-driven software architecture for a stitching system

NASA Technical Reports Server (NTRS)

Thrash, Patrick J. (Inventor); Miller, Jeffrey L. (Inventor); Pallas, Ken (Inventor); Trank, Robert C. (Inventor); Fox, Rhoda (Inventor); Korte, Mike (Inventor); Codos, Richard (Inventor); Korolev, Alexandre (Inventor); Collan, William (Inventor)

2001-01-01

Native code for a CNC stitching machine is generated by generating a geometry model of a preform; generating tool paths from the geometry model, the tool paths including stitching instructions for making stitches; and generating additional instructions indicating thickness values. The thickness values are obtained from a lookup table. When the stitching machine runs the native code, it accesses a lookup table to determine a thread tension value corresponding to the thickness value. The stitching machine accesses another lookup table to determine a thread path geometry value corresponding to the thickness value.

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.

Hardware support for software controlled fast multiplexing of performance counters

DOEpatents

Salapura, Valentina; Wisniewski, Robert W

2013-10-01

Performance counters may be operable to collect one or more counts of one or more selected activities, and registers may be operable to store a set of performance counter configurations. A state machine may be operable to automatically select a register from the registers for reconfiguring the one or more performance counters in response to receiving a first signal. The state machine may be further operable to reconfigure the one or more performance counters based on a configuration specified in the selected register. The state machine yet further may be operable to copy data in selected one or more of the performance counters to a memory location, or to copy data from the memory location to the counters, in response to receiving a second signal. The state machine may be operable to store or restore the counter values and state machine configuration in response to a context switch event.

Hardware support for software controlled fast multiplexing of performance counters

DOEpatents

Salapura, Valentina; Wisniewski, Robert W.

2013-01-01

Performance counters may be operable to collect one or more counts of one or more selected activities, and registers may be operable to store a set of performance counter configurations. A state machine may be operable to automatically select a register from the registers for reconfiguring the one or more performance counters in response to receiving a first signal. The state machine may be further operable to reconfigure the one or more performance counters based on a configuration specified in the selected register. The state machine yet further may be operable to copy data in selected one or more of the performance counters to a memory location, or to copy data from the memory location to the counters, in response to receiving a second signal. The state machine may be operable to store or restore the counter values and state machine configuration in response to a context switch event.

X-Z-Theta cutting method

DOEpatents

Bieg, Lothar F.

1993-01-12

A method for machining a workpiece. The method includes the use of a rotary cutting tool mounted on the end of a movable arm. The arm is adapted to move in a plane perpendicular to the axis of rotation of the cutting tool. The cutting tool has cutting teeth to cut chips of material off of the workpiece in a predetermined size and shape to facilitate better removal of the chips from the workpiece. The teeth can be of different type and length to permit the tool to both rough cut and finish cut the workpiece during machining. The total depth of cut is divided by the number of tool teeth, so that the longest tool always performs the finishing cut.

Stochastic subset selection for learning with kernel machines.

PubMed

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

Computer-assisted framework for machine-learning-based delineation of GTV regions on datasets of planning CT and PET/CT images.

PubMed

Ikushima, Koujiro; Arimura, Hidetaka; Jin, Ze; Yabu-Uchi, Hidetake; Kuwazuru, Jumpei; Shioyama, Yoshiyuki; Sasaki, Tomonari; Honda, Hiroshi; Sasaki, Masayuki

2017-01-01

We have proposed a computer-assisted framework for machine-learning-based delineation of gross tumor volumes (GTVs) following an optimum contour selection (OCS) method. The key idea of the proposed framework was to feed image features around GTV contours (determined based on the knowledge of radiation oncologists) into a machine-learning classifier during the training step, after which the classifier produces the 'degree of GTV' for each voxel in the testing step. Initial GTV regions were extracted using a support vector machine (SVM) that learned the image features inside and outside each tumor region (determined by radiation oncologists). The leave-one-out-by-patient test was employed for training and testing the steps of the proposed framework. The final GTV regions were determined using the OCS method that can be used to select a global optimum object contour based on multiple active delineations with a LSM around the GTV. The efficacy of the proposed framework was evaluated in 14 lung cancer cases [solid: 6, ground-glass opacity (GGO): 4, mixed GGO: 4] using the 3D Dice similarity coefficient (DSC), which denotes the degree of region similarity between the GTVs contoured by radiation oncologists and those determined using the proposed framework. The proposed framework achieved an average DSC of 0.777 for 14 cases, whereas the OCS-based framework produced an average DSC of 0.507. The average DSCs for GGO and mixed GGO were 0.763 and 0.701, respectively, obtained by the proposed framework. The proposed framework can be employed as a tool to assist radiation oncologists in delineating various GTV regions. © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Machine Tool Technology. Tutoring Strategies for Metal Workers.

ERIC Educational Resources Information Center

Anoka-Hennepin Technical Coll., Minneapolis, MN.

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

High speed metal removal

NASA Astrophysics Data System (ADS)

Pugh, R. F.; Pohl, R. F.

1982-10-01

Four types of steel (AISI 1340, 4140, 4340, and HF-1) which are commonly used in large caliber projectile manufacture were machined at different hardness ranges representing the as-forged and the heat treated condition with various ceramic tools using ceramic coated tungsten carbide as a reference. Results show that machining speeds can be increased significantly using present available tooling.

Ultra-high surface speed for metal removal, artillery shell

NASA Astrophysics Data System (ADS)

Pugh, R. F.; Walsh, M. R.; Pohl, R. F.

1981-07-01

Four types of steel (AISI 1340, 4140, 4340, and HF-1) which are commonly used in large caliber projectile manufacture were machined with five types of tools at different hardness ranges representing the as-forged and the heat-treated condition. Results show that machining speeds can be increased significantly over current practice using the present available tooling.

MACHINE COOLANT WASTE REDUCTION BY OPTIMIZING COOLANT LIFE

EPA Science Inventory

Machine shops use coolants to improve the life and function of machine tools. hese coolants become contaminated with oils with use, and this contamination can lead to growth of anaerobic bacteria and shortened coolant life. his project investigated methods to extend coolant life ...

29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.

Code of Federal Regulations, 2011 CFR

2011-07-01

... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...

29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.

Code of Federal Regulations, 2012 CFR

2012-07-01

... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...

29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.

Code of Federal Regulations, 2013 CFR

2013-07-01

... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...

29 CFR 570.34 - Occupations that may be performed by minors 14 and 15 years of age.

Code of Federal Regulations, 2014 CFR

2014-07-01

... comparative shopping. (e) Price marking and tagging by hand or machine, assembling orders, packing, and... machines shall mean all fixed or portable machines or tools driven by power and used or designed for...

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

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

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

1989-01-01

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

Micro Slot Generation by μ-ED Milling

NASA Astrophysics Data System (ADS)

Dave, H. K.; Mayanak, M. K.; Rajpurohit, S. R.; Mathai, V. J.

2016-08-01

Micro electro discharge machining is one of the most widely used advanced micro machining technique owing to its capability to fabricate micro features on any electrically conductive materials irrespective of its material properties. Despite its wide acceptability, the process is always adversely affected by issues like wear that occurred on the tool electrode, which results into generation of inaccurate features. Micro ED milling, a process variant in which the tool electrode simultaneously rotated and scanned during machining, is reported to have high process efficiency for generation of 3D complicated shapes and features with relatively less electrode wear intensity. In the present study an attempt has been made to study the effect of two process parameters viz. capacitance and scanning speed of tool electrode on end wear that occurs on the tool electrode and overcut of micro slots generated by micro ED milling. The experiment has been conducted on Al 1100 alloy with tungsten electrode having diameter of 300 μm. Results suggest that wear on the tool electrode and overcut of the micro features generated are highly influenced by the level of the capacitance employed during machining. For the parameter usage employed for present study however, no significant effect of variation of scanning speed has been observed on both responses.

A material based approach to creating wear resistant surfaces for hot forging

NASA Astrophysics Data System (ADS)

Babu, Sailesh

Tools and dies used in metal forming are characterized by extremely high temperatures at the interface, high local pressures and large metal to metal sliding. These harsh conditions result in accelerated wear of tooling. Lubrication of tools, done to improve metal flow drastically quenches the surface layers of the tools and compounds the tool failure problem. This phenomenon becomes a serious issue when parts forged at complex and are expected to meet tight tolerances. Unpredictable and hence uncontrolled wear and degradation of tooling result in poor part quality and premature tool failure that result in high scrap, shop downtime, poor efficiency and high cost. The objective of this dissertation is to develop a computer-based methodology for analyzing the requirements hot forging tooling to resist wear and plastic deformation and wear and predicting life cycle of forge tooling. Development of such is a system is complicated by the fact that wear and degradation of tooling is influenced by not only the die material used but also numerous process controls like lubricant, dilution ratio, forging temperature, equipment used, tool geometries among others. Phenomenological models available u1 the literature give us a good thumb rule to selecting materials but do not provide a way to evaluate pits performance in field. Once a material is chosen, there are no proven approaches to create surfaces out of these materials. Coating approaches like PVD and CVD cannot generate thick coatings necessary to withstand the conditions under hot forging. Welding cannot generate complex surfaces without several secondary operations like heat treating and machining. If careful procedures are not followed, welds crack and seldom survive forging loads. There is a strong need for an approach to selectively, reliably and precisely deposit material of choice reliably on an existing surface which exhibit not only good tribological properties but also good adhesion to the substrate. Dissertation outlines development of a new cyclic contact test design to recreate intermittent tempering seen in hot forging. This test has been used to validate the use of tempering parameters in modeling of in-service softening of tool steel surfaces. The dissertation also outlines an industrial case study, conducted at a forging company, to validate the wear model. This dissertation also outlines efforts at Ohio State University, to deposit Nickel Aluminide on AISI H13 substrate, using Laser Engineered Net Shaping (LENS). Dissertation reports results from an array of experiments conducted using LENS 750 machine, at various power levels, table speeds and hatch spacing. Results pertaining to bond quality, surface finish, compositional gradients and hardness are provided. Also, a thermal-based finite element numerical model that was used to simulate the LENS process is presented, along with some demonstrated results.

Optimization of Processing Parameters in ECM of Die Tool Steel Using Nanofluid by Multiobjective Genetic Algorithm.

PubMed

Sathiyamoorthy, V; Sekar, T; Elango, N

2015-01-01

Formation of spikes prevents achievement of the better material removal rate (MRR) and surface finish while using plain NaNO3 aqueous electrolyte in electrochemical machining (ECM) of die tool steel. Hence this research work attempts to minimize the formation of spikes in the selected workpiece of high carbon high chromium die tool steel using copper nanoparticles suspended in NaNO3 aqueous electrolyte, that is, nanofluid. The selected influencing parameters are applied voltage and electrolyte discharge rate with three levels and tool feed rate with four levels. Thirty-six experiments were designed using Design Expert 7.0 software and optimization was done using multiobjective genetic algorithm (MOGA). This tool identified the best possible combination for achieving the better MRR and surface roughness. The results reveal that voltage of 18 V, tool feed rate of 0.54 mm/min, and nanofluid discharge rate of 12 lit/min would be the optimum values in ECM of HCHCr die tool steel. For checking the optimality obtained from the MOGA in MATLAB software, the maximum MRR of 375.78277 mm(3)/min and respective surface roughness Ra of 2.339779 μm were predicted at applied voltage of 17.688986 V, tool feed rate of 0.5399705 mm/min, and nanofluid discharge rate of 11.998816 lit/min. Confirmatory tests showed that the actual performance at the optimum conditions was 361.214 mm(3)/min and 2.41 μm; the deviation from the predicted performance is less than 4% which proves the composite desirability of the developed models.

Application of gas-fluid atomization technology in ultrosonic vibration cutting titanium alloy workpiece

NASA Astrophysics Data System (ADS)

Zhou, Zhimin; Zhang, Yuangliang; Li, Xiaoyan; Sun, Baoyuan

2009-11-01

To further improve machined surface quality of diamond cutting titanium workpiece and reduce diamond tool wear, it puts forward a kind of machining technology with mixture of carbon dioxide gas, water and vegetable oil atomized mist as cooling media in the paper. The cooling media is sprayed to cutting area through gas-liquid atomizer device to achieve purpose of cooling, lubricating, and protecting diamond tool. Experiments indicate that carbon dioxide gas can touch cutting surface more adequately through using gas-liquid atomization technology, which makes iron atoms of cutting surface cause a chemical reaction directly with carbon in carbon dioxide gas and reduce graphitizing degree of diamond tool. Thus, this technology of using gas-liquid atomization and ultrasonic vibration together for cutting Titanium Alloy is able to improve machined surface quality of workpiece and slow of diamond tool wear.

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.

The study on dynamic properties of monolithic ball end mills with various slenderness

NASA Astrophysics Data System (ADS)

Wojciechowski, Szymon; Tabaszewski, Maciej; Krolczyk, Grzegorz M.; Maruda, Radosław W.

2017-10-01

The reliable determination of modal mass, damping and stiffness coefficient (modal parameters) for the particular machine-toolholder-tool system is essential for the accurate estimation of vibrations, stability and thus the machined surface finish formed during the milling process. Therefore, this paper focuses on the analysis of ball end mill's dynamical properties. The tools investigated during this study are monolithic ball end mills with different slenderness values, made of coated cemented carbide. These kinds of tools are very often applied during the precise milling of curvilinear surfaces. The research program included the impulse test carried out for the investigated tools clamped in the hydraulic toolholder. The obtained modal parameters were further applied in the developed tool's instantaneous deflection model, in order to estimate the tool's working part vibrations during precise milling. The application of the proposed dynamics model involved also the determination of instantaneous cutting forces on the basis of the mechanistic approach. The research revealed that ball end mill's slenderness can be considered as an important milling dynamics and machined surface quality indicator.

Investigation on Effect of Material Hardness in High Speed CNC End Milling Process.

PubMed

Dhandapani, N V; Thangarasu, V S; Sureshkannan, G

2015-01-01

This research paper analyzes the effects of material properties on surface roughness, material removal rate, and tool wear on high speed CNC end milling process with various ferrous and nonferrous materials. The challenge of material specific decision on the process parameters of spindle speed, feed rate, depth of cut, coolant flow rate, cutting tool material, and type of coating for the cutting tool for required quality and quantity of production is addressed. Generally, decision made by the operator on floor is based on suggested values of the tool manufacturer or by trial and error method. This paper describes effect of various parameters on the surface roughness characteristics of the precision machining part. The prediction method suggested is based on various experimental analysis of parameters in different compositions of input conditions which would benefit the industry on standardization of high speed CNC end milling processes. The results show a basis for selection of parameters to get better results of surface roughness values as predicted by the case study results.

Investigation on Effect of Material Hardness in High Speed CNC End Milling Process

PubMed Central

Dhandapani, N. V.; Thangarasu, V. S.; Sureshkannan, G.

2015-01-01

This research paper analyzes the effects of material properties on surface roughness, material removal rate, and tool wear on high speed CNC end milling process with various ferrous and nonferrous materials. The challenge of material specific decision on the process parameters of spindle speed, feed rate, depth of cut, coolant flow rate, cutting tool material, and type of coating for the cutting tool for required quality and quantity of production is addressed. Generally, decision made by the operator on floor is based on suggested values of the tool manufacturer or by trial and error method. This paper describes effect of various parameters on the surface roughness characteristics of the precision machining part. The prediction method suggested is based on various experimental analysis of parameters in different compositions of input conditions which would benefit the industry on standardization of high speed CNC end milling processes. The results show a basis for selection of parameters to get better results of surface roughness values as predicted by the case study results. PMID:26881267

Optimizing friction stir weld parameters of aluminum and copper using conventional milling machine

NASA Astrophysics Data System (ADS)

Manisegaran, Lohappriya V.; Ahmad, Nurainaa Ayuni; Nazri, Nurnadhirah; Noor, Amirul Syafiq Mohd; Ramachandran, Vignesh; Ismail, Muhammad Tarmizizulfika; Ahmad, Ku Zarina Ku; Daruis, Dian Darina Indah

2018-05-01

The joining of two of any particular materials through friction stir welding (FSW) are done by a rotating tool and the work piece material that generates heat which causes the region near the FSW tool to soften. This in return will mechanically intermix the work pieces. The first objective of this study is to join aluminum plates and copper plates by means of friction stir welding process using self-fabricated tools and conventional milling machine. This study also aims to investigate the optimum process parameters to produce the optimum mechanical properties of the welding joints for Aluminum plates and Copper plates. A suitable tool bit and a fixture is to be fabricated for the welding process. A conventional milling machine will be used to weld the aluminum and copper. The most important parameters to enable the process are speed and pressure of the tool (or tool design and alignment of the tool onto the work piece). The study showed that the best surface finish was produced from speed of 1150 rpm and tool bit tilted to 3°. For a 200mm × 100mm Aluminum 6061 with plate thickness of 2 mm at a speed of 1 mm/s, the time taken to complete the welding is only 200 seconds or equivalent to 3 minutes and 20 seconds. The Copper plates was successfully welded using FSW with tool rotation speed of 500 rpm, 700 rpm, 900 rpm, 1150 rpm and 1440 rpm and with welding traverse rate of 30 mm/min, 60 mm/min and 90 mm/min. As the conclusion, FSW using milling machine can be done on both Aluminum and Copper plates, however the weld parameters are different for the two types of plates.