Empirical modeling of shot peening parameters for welded austenitic stainless steel using grey relational analysis

被引:1
|
作者
Lakhwinder Singh
R. A. Khan
M. L. Aggarwal
机构
[1] YMCA University of Science & Technology,Department of Mechanical Engineering
[2] Jamia Millia Islamia,Department of Mechanical Engineering
关键词
ANOVA; Gray relational analysis (GRA); Optimization; Shot peening; Taguchi method;
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中图分类号
学科分类号
摘要
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.
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页码:1731 / 1739
页数:8
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