<article_id>JME_V3_N3_RP5</article_id>
<title>Multi-Response Optimization Of Turning Parts Using Integrated Taguchi-Grey Relational Analysis</title>
<author>Neeraj Sharma</author>
<author>Sanjeev Garg</author>
<author>Pardeep Sharma</author>
<journal>Journal on Mechanical Engineering</journal>
<issn>2249 - 0744</issn>
<volume>3</volume>
<issue>3</issue>
<first_page>31</first_page>
<last_page>36</last_page>
<keywords>Grey Relational Analysis, Metal Removal Rate, Multi Response Optimization, Surface Roughness</keywords>
<abstract>Multi-Response optimization of response variables having opposite nature is cumbersome to obtain without use of optimization techniques. In this research work, Grey relational analysis and Taguchi Design approach are used for multi response optimization of metal removal rate and surface roughness during turning of . Taguchi orthogonal array L is used to design the experiment. Signal to Noise (S/N) ratio of both responses i.e. metal removal rate 9 and surface roughness are used to calculate grey relational grade. AISI 1040 MS bars Analysis of Variance (ANOVA) is used to identify the significance of process parameters on grey relational grade and shows that feed rate and spindle speed are most significant process parameters for both the responses. The confirmation experiments show that Taguchi-Grey relation analysis can be successfully utilized to obtain the multi-response optimization.</abstract>
<date>May - July 2013</date>
<copyright>Copyright &copy; 2013 i-manager publications. All rights reserved.</copyright>
<publisher>i-manager Publications</publisher>
<article_url>http://www.imanagerpublications.com/Article.aspx?ArticleId=2369</article_url>