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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: 12.07.2017; Views: 574; Downloads: 318
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Optimization of extrusion process by genetic algorithms and conventional techniques
Zoran Jurković, Miran Brezočnik, Branko Grizelj, Vesna Mandić, 2009, original scientific article

Abstract: The purpose of this research is the determination of the optimal cold forward extrusion parameters with the minimization of tool load as objective. This paper deals with different optimization approaches in order to determine optimal values of logarithmic strain, die angle and friction factor with the purpose to find minimal tool loading obtained by cold forward extrusion process. Two experimental plans based on factorial design of experiment and orthogonal array have been carried out. Classical optimization, according to the response model of extrusion forming force, and the Taguchi approach are presented. The obtained extrusion force model as the fitness function was used to carry out genetic algorithm optimization. Experimental verification of optimal forming parameters with their influences on the forming forces was also performed. The experimental results show an improvement in the minimization of tool loading. The results of optimal forming parameters obtained with different optimization approaches have been compared and based on that the characteristics analysis (features and limitations) of presented techniques.
Keywords: metal forming, forward extrusion force optimization, design of experiments, Taguchi approach, genetic algortihm
Published: 31.05.2012; Views: 1320; Downloads: 75
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