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Empirical modeling of shot peening parameters for welded austenitic stainless steel using grey relational analysis
Lakhwinder Singh, R. A. Khan and M. L. Aggarwal
The Journal of Mechanical Science and Technology, vol. 26, no. 6, pp.1731-1739, 2012
Abstract : The attempt of this paper is to present an effective approach for the optimization of the shot peening process of welded AISI 304 austenitic
stainless steel with multi performance characteristics using Grey relational analysis (GRA) based on Taguchi orthogonal array.
Twenty-seven experimental runs are performed to determine best process parameters level. An analysis of variance (ANOVA) is carried
out to identify significant peening parameters. The response tables are obtained for analyzing the optimal levels of shot peening parameters
and major factors that affect the quality function. The multiple performance characteristics including tensile strength, surface hardness
and surface roughness are the quality functions considered for the optimization. Further mathematical models are developed using
regression analysis for the tensile strength, surface hardness and surface roughness. It will be very helpful to the engineers in deciding the
levels of the shot peening parameters for desired performance characteristics.
Keyword : ANOVA; Gray relational analysis (GRA); Optimization; Shot peening; Taguchi method |
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