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

Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Quality & Reliability Management Emerald Publishing

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

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References (46)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0265-671X
DOI
10.1108/IJQRM-06-2012-0084
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Quality & Reliability ManagementEmerald Publishing

Published: Mar 2, 2015

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