In-situ aluminum matrix composite is the innovation of high performance material technology and it has superior interfacial integrity and thermodynamic stability between the matrix and reinforcement. During synthesis, the ZrB2 particle is formed by exothermic reaction within the aluminum melt. As a result, small, fine and oxide free reinforcements are formed. Excessive temperature released from in-situ chemical reaction will facilitate the homogeneous distribution of particles in entire shape of the composites. Making the engineering components from this composite material require machining operations. Therefore, addressing the machinability issues of the composite is very important. This paper proposes an approach to optimize the machining parameters in turning of Al 6061-6% ZrB2 in-situ Metal Matrix Composite (MMC) with multiple performance characteristics by using grey relational analysis. The effect of in-situ ZrB2 reinforcement particles on machinability behavior need to be studied. The machining parameters, namely cutting speed, feed rate and depth of cut are optimized with considerations of multiple performance characteristics including surface roughness, tool wear and cutting force. It is concluded that the feed rate has the strongest effect. The confirmation experiment indicates that there is a good agreement between the estimated value and experimental value of the Grey relational grade.
EDM machining characteristics of bamboo leaf ash and alumina reinforced aluminum hybrid metal matrix composite using Multi-response optimization by grey relational analysis