Journal
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
Volume 28, Issue 6, Pages 2299-2306Publisher
KOREAN SOC MECHANICAL ENGINEERS
DOI: 10.1007/s12206-014-0520-9
Keywords
Electrical discharge diamond grinding (EDDG); Hybrid machining processes (HMPs); Multi-objective optimization (MOO); Non-dominated sorting genetic algorithm (NSGA-II)
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Hybrid machining processes (HMPs), having potential for machining of difficult to machine materials but the complexity and high manufacturing cost, always need to optimize the process parameters. Our objective was to optimize the process parameters of electrical discharge diamond face grinding (EDDFG), considering the simultaneous effect of wheel speed, pulse current, pulse on-time and duty factor on material removal rate (MRR) and average surface roughness (Ra). The experiments were performed on a high speed steel (HSS) workpiece at a self developed face grinding setup on an EDM machine. All the experimental results were used to develop the mathematical model using response surface methodology (RSM). The developed model was used to generate the initial population for a genetic algorithm (GA) during optimization, non-dominated sorting genetic algorithm (NSGA-II) was used to optimize the process parameters of EDDFG process. Finally, optimal solutions obtained from pareto front are presented and compared with experimental data.
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