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 difficult to machine using traditional machining techniques, the advanced method of electrical discharge machining (EDM) was used. On stir-casted Al-B4C-GNP composites, EDM machinability investigations were conducted. Using input parameters such pulse on time, pulse off time, and peak current for the response of material removal rate (MRR) and surface roughness, Taguchi based Desirability function Analysis was used to optimize the EDM process parameters. The optimal machining parameters have been determined by the composite desirability value obtained from the desirability function analysis, and significant contribution of parameters also be determined by analysis of variance (ANOVA).