A statistical data-based approach to instability detection and wear prediction in radial turning processes
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2018
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Abstract
Radial turning forces for tool-life improvements are studied, with the emphasis on predictive rather than preventive maintenance. A tool for wear prediction in various experimental settings of instability is proposed through the application of two statistical approaches to process data on tool-wear during turning processes: three sigma edit rule analysis and Principal Component Analysis (PCA). A Linear Mixed Model (LMM) is applied for wear prediction. These statistical approaches to instability detection generate results of acceptable accuracy for delivering expert opinion. They may be used for on-line monitoring to improve the processing of different materials. The LMM predicted significant differences for tool wear when turning different alloys and with different lubrication systems. It also predicted the degree to which the turning process could be extended while conserving stability. Finally, it should be mentioned that tool force in contact with the material was not considered to be an important input variable for the model.
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Publisher Copyright: © 2018, Polish Academy of Sciences Branch Lublin. All rights reserved.
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Radial turning , Tool-life improvement , Instability detection , Wear prediction , Linear Mixed Models , Radial turning , Tool-life improvement , Instability detection , Wear prediction , Linear Mixed Models , Safety, Risk, Reliability and Quality , Industrial and Manufacturing Engineering , Project ID , info:eu-repo/grantAgreement/EC/FP7/620134/EU/High speed metallic material removal under acceptable surface integrity for rotating frame/HIMMOVAL , info:eu-repo/grantAgreement/EC/FP7/620134/EU/High speed metallic material removal under acceptable surface integrity for rotating frame/HIMMOVAL , Funding Info , The work was performed as a part of the HIMMOVAL (Grant Agreement Number: 620134) project within the CLEAN-SKY program, linked to the SAGE2 project for geared open-rotor development and the delivery of the demonstrator part. Funding through grant IT900-16 is also acknowledged from the Basque Government Department of Education, Universities and Research. , The work was performed as a part of the HIMMOVAL (Grant Agreement Number: 620134) project within the CLEAN-SKY program, linked to the SAGE2 project for geared open-rotor development and the delivery of the demonstrator part. Funding through grant IT900-16 is also acknowledged from the Basque Government Department of Education, Universities and Research.
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Jimenez Cortadi , A , Irigoien , I , Boto , F , Sierra , B , Suarez , A & Galar , D 2018 , ' A statistical data-based approach to instability detection and wear prediction in radial turning processes ' , Eksploatacja i Niezawodnosc - Maintenance and Reliability , vol. 20 , no. 3 , pp. 405-412 . https://doi.org/10.17531/ein.2018.3.8