Optimisation of EDM process parameters: by butterfly optimisation algorithm and genetic algorithm Online publication date: Tue, 27-Sep-2022
by Shubham Jain; Vishal Parashar
International Journal of Computational Materials Science and Surface Engineering (IJCMSSE), Vol. 11, No. 1, 2022
Abstract: In this paper, parametric single-objective optimisation and multi-objective optimisation for electric discharge machining (EDM) on En-24 steel has been carried out by butterfly optimisation algorithm (BOA) and Genetic Algorithm. In this research, different process parameters like Peak Current (Ip), Pulse ON Time (Ton), Gap Voltage (Vp) have been selected to optimise the responses like material removal rate (MRR) and surface roughness. A central composite design (CCD), for three machining parameters at five-level each, has been selected to design the experiments. Analysis of variance (ANOVA) has been performed to find significant process parameters affecting responses and the validity of the derived modal in the present work. The grey relational analysis method has been used to find the optimum weightage for all responses. The comparison found that the BOA gives very close results to the Genetic Algorithm so that BOA can be applied for real-world optimisation problems.
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