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Optimization of machining parameters for turning operation with multiple quality characteristics using Grey relational analysis
Franko Puh, Zoran Jurković, Mladen Perinic, Miran Brezočnik, Stipo Buljan, 2016, original scientific article

Abstract: Optimization of machining processes is essential for achieving of higher productivity and high quality products in order to remain competitive. This study investigates multi-objective optimization of turning process for an optimal parametric combination to provide the minimum surface roughness (Ra) with the maximum material-removal rate (MRR) using the Grey–Based Taguchi method. Turning parameters considered are cutting speed, feed rate and depth of cut. Nine experimental runs based on Taguchi’s L9 (34) orthogonal array were performed followed by the Grey relational analysis to solve the multi- response optimization problem. Based on the Grey relational grade value, optimum levels of parameters have been identified. The significance of parameters on overall quality characteristics of the cutting process has been evaluated by the analysis of variance (ANOVA). The optimal parameter values obtained during the study have been validated by confirmation experiment.
Keywords: ANOVA, Grey relational analysis, multi-objective optimization, Taguchi method, turning
Published in DKUM: 12.07.2017; Views: 1346; Downloads: 400
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