Title: Optimisation of ECM parameters using RSM and non-dominated sorting genetic algorithm (NSGA II)

Authors: C. Senthilkumar; G. Ganesan; R. Karthikeyan

Addresses: Department of Manufacturing Engineering, Annamalai University, Annamalai Nagar – 608 002, Tamilnadu, India ' Department of Manufacturing Engineering, Annamalai University, Annamalai Nagar – 608 002, Tamilnadu, India ' BITS Pilani, Dubai Campus, Dubai International Academic City, P.O. Box No. – 345055, Dubai, UAE

Abstract: Metal matrix composites (MMC) are hard to machine due to the presence of hard and brittle ceramic reinforcements. Electro chemical machining (ECM) is an important process for machining such materials. Being a complex process, it is very difficult to determine optimal parameters for improving cutting performance. The objective of this research is to study the effect of electrolyte flow rate, applied voltage, electrolyte concentration, and tool feed rate on metal removal rate (MRR) and surface roughness (Ra). In the present work, response surface methodology (RSM) and a multi-objective optimisation method based on a non-dominated sorting genetic algorithm (NSGA-II) is used to optimise ECM process. A non-dominated solution set has been obtained and reported.

Keywords: composite materials; response surface methodology; RSM; metal removal rate; MRR; surface roughness; surface quality; ECM parameters; electrochemical machining; non-dominated sorting genetic algorithms; NSGA II; metal matrix composites; MMC; electrolyte flow rate; applied voltage; electrolyte concentration; tool feed rate.

DOI: 10.1504/IJMMM.2013.055130

International Journal of Machining and Machinability of Materials, 2013 Vol.14 No.1, pp.77 - 90

Received: 10 Apr 2012
Accepted: 19 Oct 2012
Published online: 26 Dec 2013 *

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