Friction stir welding, 6061 and 5083 aluminum alloys, Response surface optimization algorithm, Genetic optimization algorithm, Particle swarm optimization algorithm, Technology

In this study, the friction stir welding process has been investigated for joining dissimilar 6061 aluminum alloy to 5083 aluminum alloy. Cutting and cleaning of the surface of the samples have been performed for friction stir welding. By evaluating the feasibility of friction stir welding of dissimilar 6061 and 5083 aluminum alloys to each other and welding them, the samples were examined to investigate mechanical properties. Tensile testing was used to investigate mechanical properties. After performing mechanical property tests, optimization of friction stir welding process parameters on tensile strength and weld yield strength was carried out with artificial intelligence. Response surface methodology, genetic algorithms, and particle swarm optimization algorithms have been used to optimize welding parameters. The results of the tensile test showed an improvement in the ultimate strength and yield strength of welded samples at a tool rotational speed of 800 rpm and a tool traverse speed (welding speed) of 100 mm/min with an ultimate tensile strength of 199 MPa. The effect of welding parameters such as tool rotational speed and tool traverse speed has also been investigated through optimization. The optimal process parameters to maximize tensile strength and yield strength were obtained at a rotational speed of 630 rpm and a tool welding speed of 128 mm/min. The maximum yield strength in the weld zone for the combination of the optimal parameters of the process was obtained at 126 MPa, and the maximum tensile strength in the weld zone was obtained at 172 MPa.