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FSW (Friction stir welding) is a sort of a solid-state joining process in which a non-consumable tool is used to join analogous or divergent materials. The input parameters like TRS (tool rotational speed), welding velocity, axial force of FSW play an extremely indispensable role in obtaining the weld joint quality. The quality of weld joint can be interpreted considering weld macrographs and mechanical properties like tensile strength, hardness, etc. Various traditional and advanced optimization methods are applied with an objective of gaining a virtuous weld-joint with the anticipated mechanical properties. Nowadays, advanced optimization methods like Neuro-Fuzzy, ANN, etc. are utilized to envisage the optimal process parameters of FSW. The prediction of optimal process conditions in welding processes, results into desired weld joint quality. A detailed survey of the utilization of these approaches in the domain of FSW process parameters optimization and prediction to enhance mechanical properties of the friction stir welded joints has been introduced herein.
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