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

This research shows how Multicoated hard metal inserts with sculptured rake face geometry may anticipate tool wear in hard turning of 817M40 (EN 24) steel material with 48 HRC on a conventional lathe. Tool wear becomes a significant factor in the surface quality of produced items with hard turning. In order to predict tool wear, an effort is made to combine cutting force, cutting temperature, and tool vibration (displacement) with cutting velocity, feed, and depth of cut. In this study, Taguchi L18 orthogonal array (mixed design) optimization was utilised to optimise various cutting parameters such as cutting velocity, feed, and depth of cut using Minitab software. Furthermore, the outcomes of the Design of Experiment are compared to the ANOVA Response Surface approach (RSM). Response surface methodology (RSM) and Analysis of Variance (ANOVA) yield results that are remarkably similar to those obtained by Design of Experiment (DoE).

Author(S) Details

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.

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