Machining of aluminium-based metal matrix composite - a particle swarm optimisation approach

Abstract

Machining performance of 5 wt.% silicon carbide particulate reinforced Al 7075 matrix composite was investigated in terms of cutting tool temperature (T), average surface roughness (Ra) and tool flank wear (VBc) during turning in pollution-free air water spray cooling environment. Metal was removed by multiple layers of TiN coated carbide inserts during turning. Nonlinear regression models were developed and their adequacies were verified. Significance of process parameters on the responses was investigated through analysis of variance. The responses were optimized individually using Taguchi technique and then simultaneously through particle swarm optimisation technique. The proposed multi-objective algorithm outperformed the traditional Taguchi approach and effectively resulted to a group of non-dominated solutions. Pareto optimal fronts were compiled and plotted for T, Ra and VBc, which can be selected according to the production requirements.