Application of Grey Relational Analysis Along with Principal Component Analysis for Multi-Response Optimization of Hard Turning
Citation
Suha K. Shihab, Zahid A. Khan, Arshad Noor Siddiquee"Application of Grey Relational Analysis Along with Principal Component Analysis for Multi-Response Optimization of Hard Turning", International Journal of Engineering Trends and Technology (IJETT), V38(5),238-245 August 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
Investigation on the effect of cutting speed, feed
rate, depth of cut and different cutting conditions on the
machining force components and surface roughness during
hard turning of AISI 52100 has been presented in this paper.
Nine turning experiments as per Taguchi’s standard L9
orthogonal array were performed on AISI 52100 hard alloy
steel using a CNC lathe machine and cutting force
component as well as surface roughness were measured.
Subsequently, multi-response optimization was performed by
employing grey relational and principal component
analyses. The results revealed that grey relational analysis
along with the principal component analysis is a simple as
well as effective method for solving the multi-response
optimization problem and it provides the optimal
combination of hard turning parameters. Further, the
analysis of variance (ANOVA) was also employed to identify
the most significant parameter based on percentage of
contribution of each machining parameter.
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Keywords
Hard turning, Optimization, Taguchi
method, Grey relational analysis, Principal
component analysis.