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Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector regression techniques

Jaganathan Gokulachandran (Department of Mechanical Engineering, Amrita School of Engineering, Coimbatore, India)
K. Mohandas (Department of Mechanical Engineering, Amrita School of Engineering, Coimbatore, India)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 2 March 2015

Abstract

Purpose

The accurate assessment of tool life of any given tool is a great significance in any manufacturing industry. The purpose of this paper is to predict the life of a cutting tool, in order to help decision making of the next scheduled replacement of tool and improve productivity.

Design/methodology/approach

This paper reports the use of two soft computing techniques, namely, neuro-fuzzy logic and support vector regression (SVR) techniques for the assessment of cutting tools. In this work, experiments are conducted based on Taguchi approach and tool life values are obtained.

Findings

The analysis is carried out using the two soft computing techniques. Tool life values are predicted using aforesaid techniques and these values are compared.

Practical implications

The proposed approaches are relatively simple and can be implemented easily by using software like MATLAB and Weka.

Originality/value

The proposed methodology compares neuro – fuzzy logic and SVR techniques.

Keywords

Acknowledgements

The authors wish to thank the chairman, department of mechanical engineering, Amrita Vishwa Vidyapeetham for providing work shop facilities to carry out their experimental work.

Citation

Gokulachandran, J. and Mohandas, K. (2015), "Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector regression techniques", International Journal of Quality & Reliability Management, Vol. 32 No. 3, pp. 270-290. https://doi.org/10.1108/IJQRM-06-2012-0084

Publisher

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Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited