Studies on Optimization of Tool Wear in Hard Turning of EN 24 Steel Using DoE and Verification through ANOVA and RSM

Authors

  • G. Ragul Department of Mechanical Engineering, Budge Budge Institute of Technology, Kolkata, India.
  • Pallab Roy Department of Mechanical Engineering, Budge Budge Institute of Technology, Kolkata, India.
  • Arjit Ganguly Mechatronics, Warsaw University of Technology, Poland.
  • Sandip Ghosh Department of Mechanical Engineering, JIS College of Engineering, Kalyani, India.
  • S. Sankar Department of Mechanical Engineering, Nehru College of Engineering & Research Centre, Kerala, India.
  • Abhijit Roy Department of Mechanical Engineering, Budge Budge Institute of Technology, Kolkata, India.

DOI:

https://doi.org/10.9734/bpi/nper/v4/12899D

Keywords:

Tool wear, hard turning, Minitab, response surface methodology, analysis of variance

Abstract

This paper depicts about prediction of tool wear in hard turning of 817M40 (EN 24) steel material with 48 HRC at conventional lathe using Multicoated hard metal inserts with sculptured rake face geometry. In hard turning, tool wear becomes an important parameter affecting the surface quality of finished parts.  Also, an effort is made to bring together the cutting force, cutting temperature and tool vibration (displacement) in conjunction with cutting velocity, feed and depth of cut to foresee the tool wear. Taguchi L18 orthogonal array (mixed design) optimization using Minitab software was used in this work to optimise various cutting parameters such as cutting velocity, feed, and depth of cut. Furthermore, the Design of Experiment results are weighed against the Analysis of Variance (ANOVA) Response Surface methodology (RSM). The result obtained from Response surface methodology (RSM) and Analysis of Variance (ANOVA) conforms very strongly to the results obtained by Design of Experiment (DoE).

Published

2021-12-02

How to Cite

G. Ragul, Pallab Roy, Arjit Ganguly, Sandip Ghosh, S. Sankar, & Abhijit Roy. (2021). Studies on Optimization of Tool Wear in Hard Turning of EN 24 Steel Using DoE and Verification through ANOVA and RSM. Novel Perspectives of Engineering Research Vol. 4, 169–176. https://doi.org/10.9734/bpi/nper/v4/12899D

Issue

Novel Perspectives of Engineering Research Vol. 4

Section

Chapters