Optimization of Machining Parameters Based on Desirability Function Analysis for Stir Casted Aluminium Hybrid Metal Matrix Composites

These days, aluminum and other material composites are indispensable for a wide range of engineering applications, including automotive-related ones. The machinability investigations of hybrid metal matrix composites (HMMC) made of Al 6061 are reported in this paper. Graphene nanoparticles (GNp) and boron carbide were used to reinforce Al6061 alloy for the experiment. Stir casting was used to create the hybrid composite under the right circumstances. Since HMMC is not easy to machine using conventional machining procedures, the advanced method of electrical discharge machining (EDM) was used. EDM machinability studies were carried out on stir-casted Al-B4C-GNP composite materials to examine the effects of wire EDM machining variables, including current, pulse on, and pulse off, on surface roughness and material removal rate. Taguchi based Desirability function Analysis was used to optimize the EDM process parameters for maximization of the material removal rate (MRR) and minimization of the surface roughness responses. The desirability function analysis yielded the composite desirability value, which was used to estimate the ideal machining parameters. Analysis of variance (ANOVA) was also used to determine the components that contributed significantly.