Multi-response optimization of CNC turning parameters of austenitic stainless steel 303 using Taguchi-based grey relational analysis-Reference-Cited by-同舟云学术

Multi-response optimization of CNC turning parameters of austenitic stainless steel 303 using Taguchi-based grey relational analysis

Published:2020-12-01 Issue:4 Volume:44 Page:592-601
ISSN:0315-8977
Container-title:Transactions of the Canadian Society for Mechanical Engineering
language:en
Short-container-title:Trans. Can. Soc. Mech. Eng.

Author:

Sundara Bharathi S.R.¹²,Ravindran D.¹²,Moshi A. Arul Marcel¹²

Affiliation:

1. Department of Mechanical Engineering, National Engineering College, Kovilpatti, Tamil Nadu 628 503, India

2. Department of Mechanical Engineering, National Engineering College, Kovilpatti, Tamil Nadu 628 503, India.

Abstract

Extensive research has been carried out to optimize the process parameters of several machining processes. Optimizing the influencing parameters of the turning operation is a precise action that determines the desired level of quality. This study focuses on the multi-criteria optimization of the CNC turning process parameters of stainless steel 303 (SS 303) material to achieve minimum surface roughness (Ra) with maximum material removal rate (MRR) by means of Taguchi-based grey relational analysis. A CNC machine was tested following Taguchi’s L9 orthogonal array design. Grey relational analysis was used as the multi-criteria optimization tool. The significance of each individual process parameter on the overall characteristics of the turned specimen was estimated using analysis of variance (ANOVA). Regression equations were generated using the input factors with the selected output parameters. In addition, a morphological study of the chips produced by the turning process was carried out using SEM images in order to relate the chip geometry with the output responses.

Publisher

Canadian Science Publishing

Subject

Mechanical Engineering

Link

https://cdnsciencepub.com/doi/pdf/10.1139/tcsme-2019-0254

Reference18 articles.

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