Optimizing wire electrical discharge machining performance of Inconel 625 with genetic algorithms & particle swarm optimization

Abstract

In the present work, the Inconel 625 material is utilized for processing on a wire electrical discharge machine. The zinc-coated brass wire is used as a tool electrode. The Taguchi mixed orthogonal L27 experimental design is developed to perform the experiments. The parameter was induced on normal and cryogenic material such as pulse on time (Ton), pulse off time (Toff), discharge current (Ip), wire feed (Wf), and wire tension (WT). The characteristics responses i.e., material removal rate (MRR), surface roughness (Ra), and overcut (OC) were analyzed. The genetic algorithm (GA) was applied for the evaluation and measuring of fact, which determined its performance, and predicted facts were considered for particle swarm optimization (PSO) technique multiple objective problems. After the comparison, the facts predicted were analyzed for the response, which revealed the surface integrity and accuracy on the machined surface. The solution implied that applied PSO gives highly significant results on optimal setting parameters of WEDM machining. The 0.419 μm surface roughness has been obtained by a cryogenic process as compared to normal (0.880 μm). The material removal rate for the cryogenic process was found to have decreased in PSO by 21.18 % and in GA by 2.78 % in comparison to the normal process. The obtained results give the utmost measure for the suitability of time reduction and cost-cutting in productivity rate.

Keywords

• Cryogenic
• PSO
• Genetic algorithm
• WEDM