Predictive Modeling and Optimization of Technological Response Parameters in Nd:YAG Laser Microgrooving of Titanium Alloy Using Combined RSM-PSO Approach

Abstract

The present work focuses on modeling and optimization during Nd:YAG laser microgrooving of Ti6Al4V titanium alloy material with an objective to find the optimum process parameters settings for the groove upper width as well as depth and heat-affected zone. The experiments are performed as per Box–Behnken design of experiments (BBDOEs) with four process parameters (diode current, pulse frequency, scanning speed, and number of passes) for parametric optimization in order to control the technological response characteristics of the precision microgrooves on Ti6Al4V titanium alloy. Analysis of variance (ANOVA), response surface methodology (RSM) and particle swarm optimization (PSO) are subsequently proposed for predictive modeling and process optimization. The methodology described here is expected to be highly beneficial for manufacturing industries.