Table of Contents
International Scholarly Research Notices
Volume 2014 (2014), Article ID 905828, 10 pages
http://dx.doi.org/10.1155/2014/905828
Research Article

Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

School of Mechanical Engineering, KIIT University, Bhubaneswar, India

Received 30 April 2014; Accepted 15 July 2014; Published 30 October 2014

Academic Editor: Wilma Polini

Copyright © 2014 Arun Kumar Parida and Bharat Chandra Routara. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Taguchi’s design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (), feed (), and depth of cut (), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (). The machining is conducted with Taguchi L9 orthogonal array, and based on the analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, . Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, . Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach.