Application of Taguchi-Based Grey System for Multi Aspects Optimization on Wire Electric Discharge Machining of Aluminum-Graphene Nanoplatelets Composites

Aluminum Metal Matrix Composite (AMMC) materials have loftier individualities and are known as an alternative material for a range of aerospace and automotive engineering applications. Reinforcement inclusion makes the components tougher, resulting in low performance of machining by traditional conservative machining practices. The present study presents a detailed review of the machinability of AMMC (Pure Aluminum + Graphene nanoplatelets) using Wire Electric Discharge Machining (WEDM). For WEDM of AMMC, a multi-objective optimization method is proposed to evaluate possible machining parameters in order to achieve better machining efficiency. Taguchi’s approach to the design of experiments is used to organize the experiments. For performing experiments, an L₂₇ orthogonal array was selected. Five input process variables were considered for this study. The Grey Relational Analysis (GRA) is used to achieve the best features of multi-performance machining. The experimental results show that the proposed multi-objective optimization approach greatly improves the features of multi-performance machining.