WSEAS Transactions on Applied and Theoretical Mechanics
Print ISSN: 1991-8747, E-ISSN: 2224-3429
Volume 10, 2015
Optimization of Material Removal Rate of AlMg1SiCu in Turning Operation using Genetic Algorithm
Authors: ,
Abstract: In the present study genetic algorithm was used to optimize the turning process parameters to obtain maximum material removal rate. The prediction of optimal machining condition for material removal rate plays an important role in process planning. Thus the objective of present study was to develop an empirical model to predict material removal rate in terms of spindle speed, feed rate and depth of cut using multiple regressions modeling method. Experiments were carried out on NC controlled machine tool by taking AlMg1SiCu as workpiece material and carbide inserted cutting tool. Finally, genetic algorithm has been employed to find out the optimal setting of process parameters that optimize material removal rate. The best response value for material removal rate obtained from single objective optimization by genetic algorithm was 6021.411 mm3/min. Comparisons of experimental and predicted results at optimum conditions showed an error of 3.35 %.This provides flexibility to the manufacturing industries to choose the best setting depending on applications.
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Keywords: Genetic algorithm, Aluminum alloy, Taguchi approach, Analysis of variance, Regression modeling, Material removal rate
Pages: 95-101
WSEAS Transactions on Applied and Theoretical Mechanics, ISSN / E-ISSN: 1991-8747 / 2224-3429, Volume 10, 2015, Art. #10