Process Parameter Optimization for Abrasive Water Jet Machining of Titanium Alloy Using Meta-Heuristic Algorithms

Abstract

Recently, the trend of optimization algorithms for improvements of surface quality and productivity characteristics in abrasive water jet machining of titanium alloy (Ti-6Al-4V alloy) has become increasingly more widespread in various industrial sectors i.e., aircraft and automobile Industries. Here, the present research attempts to select the ideal or best AWJM process parameters by implementing the well known meta-heuristic algorithm i.e., Teacher learning based optimization method (TLBO). The AWJM experiments as per the Taguchi L9 orthogonal array were performed on Ti 6Al-4V titanium alloy by considering jet transverse speed, stand-off distance and abrasive flow as the input parameters. Then, the influence of process parameters on surface roughness and material removal rate has been performed by means plot and ANOVA analysis. After that, the results are optimized with the TLBO method. The overall results indicate that the TLBO method is an efficient method used to find the optimal results with very short interval of time i.e., within 3 sec.