Publication Type:

Journal Article

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

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.

Notes:

cited By (since 1996)0; Article in Press

Cite this Research Publication

Dr. Gokulachandran J., Mohandas, K., 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.

207
PROGRAMS
OFFERED
5
AMRITA
CAMPUSES
15
CONSTITUENT
SCHOOLS
A
GRADE BY
NAAC, MHRD
9th
RANK(INDIA):
NIRF 2017
150+
INTERNATIONAL
PARTNERS