Modelling of Tool Wear for Ti64 Turning Operation

Abstract:

In this study, an attempt has been made to develop a predictive model for tool nose wear. A well planned experimental design was utilized for this purpose using the design of experiment approach. From this research work, it was found that cutting speed (s), feed (f) and their interaction having the main effect on cutting tool performance. Using ANOVA analysis significance and contribution of each machining parameter and their interaction is also analyzed. Hence, a predictive model was developed to predict tool nose wear by using the various machining parameters and its adequacy was also checked for the prediction purpose.

• Periodical: Materials Science Forum (Volume 969)
• Pages: 750-755
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.969.750
• Online since: August 2019
• Authors: Pawan Kumar*, J.P. Misra
• Keywords: Modelling, Response Surface Methodology, Titanium Alloy, Tool Wear, Turning

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