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Comparative study of two soft computing techniques for the prediction of remaining useful life of cutting tools

Publication Type : Journal Article

Publisher : Journal of Intelligent Manufacturing

Source : Journal of Intelligent Manufacturing, Volume 26, Number 2, p.255-268 (2013)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84876793216&partnerID=40&md5=16307036bca9df9e0687b87c62c881e8

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2013

Abstract : Reuse of partially worn-out materials and parts is a philosophy now being applied in all manufacturing industries to achieve the goal of green manufacturing. High productivity cutting tools used in manufacturing industry are generally expensive. As such, the accurate assessment of remaining useful life (for reuse) of any given tool is of great significance in any manufacturing industry. This exercise will in turn reduce the overall cost and help achieve enhanced productivity. This paper reports the use of two soft computing techniques, namely, neuro fuzzy logic technique and support vector regression technique for the assessment of remaining useful life (RUL) of cutting tools. In this work, experiments are conducted based on Taguchi approach and tool life values are obtained. Tool life values are predicted using the aforesaid two soft computing techniques and RUL obtained from these values are compared. © 2013 Springer Science+Business Media New York.

Cite this Research Publication : Dr. Gokulachandran J., K. Mohandas, and Dr. Padmanaban R., “Comparative study of two soft computing techniques for the prediction of remaining useful life of cutting tools”, Journal of Intelligent Manufacturing, vol. 26, pp. 255-268, 2013.

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