Friction welding is a type of solid state welding which plays an important role in joining metal surfaces with the help of frictional heat accompanied with high force. Optimization of process parameters of friction welding is important for all types of materials. Optimization of input parameters of friction welding also plays a very significant role in determining the quality of a weld joint. Purpose of this study is to optimize the welding process parameters in friction welding of AISI 904L super austenitic stainless steel by using regression analysis and evolutionary algorithms. This study is to determine optimimum welding process parameters of friction welding with the help of genetic algorithm (GA) and simulated annealing (SA). Also, it explains how to obtain near optimum welding conditions in a wide range by conducting a relatively small number of experiments. Results of these evolutionary computational techniques were compared with experimental results. Finally, an optimization parameter is obtained for a maximum fatigue life and a minimum welding time.
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