The Multi-Objective Optimization of the Friction Stir Welding using the Taguchi Design Method, the Response Surface Model and the Particle Swarm Algorithm

The friction stir welding method was first developed in 1991 at the British Welding Institute as a solid-state bonding method and employed for welding aluminum alloys. This method has high energy efficiency and good compatibility with the environment. In general, the frictional stir welding process is suitable for metals with a low melting point, whose melting welding is not of good quality. In this research, multi-objective optimization of the mechanical properties in the friction welding of AH12 1050 aluminum alloy has been performed experimentally using a combination of response surface methods and multi-objective particle swarm optimization. The Taguchi method has also been utilized to design experiments with two types of threaded cylindrical and simple tapered pins. Pin diameter, shoulder diameter, tool rotational speed, tool feed, and tool deviation angle are selected as the process variables. Specimen strength, toughness, and hardness are considered as objective functions. The optimization results and a prediction accuracy of more than 93%, show a good agreement between the surface prediction model and the experiments despite the complexity of the process.