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

ABSTRACT: 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. Threaded and simple conical pins are utilized to evaluate the effect of the pin geometry on the specimen mechanical properties. Optimization model outputs are in agree with the obtained experimental results. The effects of process parameters on the mechanic

SUBMITTER: Kahhal P 

PROVIDER: S-EPMC8857264 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature