Multi-objective optimization of drilling of Al5059-SiC-2%MoS2 composites using NSGA-II

Abstract

Abstract The drilling process is a broadly renowned conventional machining process which has the capacity to produce a hole on the components. The aluminum alloy of A15059 matrix is reinforced with the two different reinforcement particles such as silicon carbide (SiC) and molybdenum disulphide (MoS2). SiC particles are varied at three different sizes such as 10, 20 and 40 µm and three different weight percentages such as 5, 10 and 15%. MoS2 is added in all composites at a constant level of 2 wt%. The input process parameters considered for this investigation are spindle speed, feed rate, the particle size of SiC and weight percentage of SiC and output parameters such as metal removal rate (MRR) and temperature are studied. The present work is to optimize the drilling parameters of aluminium metal matrix composites using Non-dominated sorting genetic algorithm II (NSGA-II) technique. The drilling experiments are conducted based on Taguchi L27 orthogonal design. At the end, the optimal setting of drilling process parameters is found using NSGA-II that simultaneously maximizes MRR and minimizes temperature. The set of Pareto-optimal front offers flexibility to the manufacturing industries to select better drilling conditions depending on applications.