Optimizing process parameters for laser beam micro-marking using genetic algorithm and particle swarm optimization

Abstract

Laser micro-marking is an efficient technique for permanent marking and logo printing on materials. This study details the selection of an optimal parametric combination for laser micro-marking. In this work, markings were performed on Gallium Nitride (GaN) with varying the levels of marking parameters. The parameters considered in the present work are current (A), pulse frequency (Hz), and scanning speed (mm/sec). This experiment was designed using a “central composite design,” grounded in the response surface methodology. Mark intensity, which is a prominent response in laser marking, was considered the output response. The data interpretation involved analysis of variance (ANOVA) and mathematical modelling between the input parameters. It is essential to determine the relationship and significance of input-output variation. The interaction effect of various input parameters on mark intensity was also studied. Finally, two techniques, namely genetic algorithm (GA) and particle swarm optimization (PSO), were applied, and the optimal settings of input constraints were predicted.