Abstract

Friction stir welding (FSW) has many advantages when compared with another fusion welding. The experimental analysis and optimization of friction stir welding (FSW) were done to obtain desired mechanical properties of dissimilar aluminum welded plates (2024T3 and 7075T6). The friction stir welding process was done on aluminum plates (2024T3 and 7075T6) for different three rotating speeds (710, 1120 and 1800), three welding speeds (25, 50 and 77), three different steel tools (Square, cylindrical and Hexagonal) and 2° title angle. The different tests of welding were done according to the orthogonal matrix of experimental design analysis, then a tensile test was done to calculate the ultimate stress to get the welding efficiency. The optimum welding environment led to the maximum efficiency was obtained by these methods (Taguchi, Particle Swarm Optimization and new modified Particle Swarm Optimization). Particle swarm optimization (and its new modification) used an artificial neural network to find the relation between the input and output parameters. The results showed that when the rotating speed is increased and welding speed is decreased (but this conclusion depends on tool shape) the welding efficiency is increased. The present study showed that the modified PSO is the best method to find the optimum welding environment as compared with experimental results

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