Optimization of Laser Welding Parameters of Aluminium Alloy 2024 using Particle Swarm Optimization Technique

Abstract

Laser welding is a viable method of joining aluminium alloys. The input parameters employed in the welding process have a significant impact on the weld quality. There are several parameters that influence weld quality, however, describing their relationship with weld seam characteristics is challenging. This study uses the Taguchi approach and particle swarm optimization (PSO) techniques for improving the weld quality in an Al 2024 lap joint to achieve a consistent and reliable joint. The experiments are performed on a laser welding machine following an L9 orthogonal array experimental design with peak power, scanning speed, and frequency as input parameters. Here, breaking load, bond width and throat length are considered as the responses. Experimentally a maximum breaking load of 1233 N and a minimum bond width of 398.81 µm is achieved. The throat length ranged from 340.72 µm to 983.94 µm. Regression analysis is used to establish the relationship between the input and the responses. The regression equations are utilized as the objective function in an optimization problem. The crowding distance PSO is used to acquire the global optima. Finally, the optimal process parameters for achieving the desired goals are presented.