Publication Type : Journal Article
Publisher : International Journal of Productivity and Quality Management
Source : International Journal of Productivity and Quality Management, Volume 9, Number 4, p.502-518 (2012)
Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84862211300&partnerID=40&md5=e3db13c43ab8880dfb9a6e7a9eecfdd8
Campus : Coimbatore
School : School of Engineering
Department : Mechanical Engineering
Verified : Yes
Year : 2012
Abstract : In manufacturing industry, cutting tools are often discarded when much of their potential life still remains. Predicting the remaining useful life of the partially degraded components and putting them to use will help to save natural resources to a great extent. This saves manufacturing cost and protects environment. The main objective of this research is to develop a comprehensive methodology to assess the reuse potential of carbide-tipped tools. In this work, based on Taguchi approach, experiments are conducted and tool life values are obtained. The analysis is carried out in two stages. In the first stage, a regression model is proposed for the prediction of remaining life of carbide-tipped tools. In the second stage, an artificial neural network model is developed for predicting tool life. The results of both models are compared. © 2012 Inderscience Enterprises Ltd.
Cite this Research Publication : Dr. Gokulachandran J. and K. Mohandas, “Predicting remaining useful life of cutting tools with regression and ANN analysis”, International Journal of Productivity and Quality Management, vol. 9, pp. 502-518, 2012.
