Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector regression techniques
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
:Emerald Group Publishing Limited
Copyright © 2015, Emerald Group Publishing Limited