Title: Multi-objective optimisation of electrical discharge machining of metal matrix composite Al/SiC using non-dominated sorting genetic algorithm

Authors: Abolfazl Golshan; Scott Gohery; Amran Ayob

Addresses: Department of Mechanical Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43300, Serdang, Selangor, Malaysia. ' Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310, UTM Skudai, Malaysia. ' Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310, UTM Skudai, Malaysia

Abstract: In this research, the influence of electrical discharge machining (EDM) on surface roughness and material removal rate (MRR) in metal matrix composite Al/SiC composite was investigated. With use of experimental result analysis and mathematical modelling, the correlation between four EDM conditions and process outputs were studied. Four investigated EDM conditions included pulse on-time, pulse peak current, average gap voltage and percent volume fraction of SiC. For finding optimal conditions, outputs extracted from non-dominated sorting genetic algorithm (NSGA-II) led in achieving appropriate models. The optimisation results showed suggested method has a high performance in problem solving.

Keywords: electrical discharge machining; EDM; metal matrix composites; MMC; aluminium; silicon carbide; DOE method; surface roughness; surface quality; material removal rate; MRR; non-dominated sorting genetic algorithms; NSGA-II; design of experiments; electro-discharge machining; multi-objective optimisation.

DOI: 10.1504/IJMMS.2012.049972

International Journal of Mechatronics and Manufacturing Systems, 2012 Vol.5 No.5/6, pp.385 - 398

Received: 01 Aug 2011
Accepted: 22 Jan 2012
Published online: 21 Aug 2014 *

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