A multi-objective optimization using response surface model coupled with particle swarm algorithm on FSW process parameters.

In this study, multi-objective optimization of mechanical properties in friction-stir-welding of AH12 1050 aluminum alloy is performed using a combination of the response surface method and multi-objective particle swarm optimization algorithm. The process parameters are considered as tool pin diameter, shoulder diameter, rotational speed, feed speed, and tool tilt angle. The heat-affected zone's yield strength, fracture strain, impact toughness, and hardness on the advancing and retreating sides are selected as the objective functions.