Friction stir welding (FSW) grabs more attention since the past decade among the researchers worldwide due to its excellent characteristics such as no emission of fumes, no filler material, comparatively economical and so on. Friction stir welding is effectively used in bringing better joint without any appreciable defects in light materials such as Aluminium, Magnesium etc., Experiments in FSW of materials with high density such as steel, copper alloys etc., have also been tried out. The selection of proper welding parameters determines a good weldment. In this work, Aluminium matrix hybrid composite was manufactured through stir casting with the matrix AA7010 and reinforcements SiC and Al₂O_3. The hybrid composite workpieces were subjected to friction stir welding process by varying the process parameters such as tool rotation speed, welding speed and axial force using Taguchi L27 orthogonal array. Tensile strength of FS welded composite was examined and regression analysis was done. Genetic Algorithm technique was used to optimize the weld tensile strength within the design space of 5³ = 125 alternatives of parametric combinations. The study focuses on the improvement of the tensile strength of the welded specimens.

Keywords: Hybrid composite, Friction stir welding, Optimization, Genetic algorithm, Tensile strength