Model based optimisation of friction stir welding processes

Abstract

This paper proposes a model based approach for the optimisation of friction stir welding processes. The proposed approach starts with building a model of the process. For this study, the thermal model developed by Chao and his associate for friction stir welding of AA 2195-T8 is replicated using Fluent. Once developed, the thermal model is then used to simulate the process. Two surrogate models, one linear and one non-linear, are constructed to relate three process parameters with maximum temperature at a selected location, using the simulation data generated by the thermal model. A constrained optimisation model is next formulated, which is eventually solved by five population based metaheuristrics to find the optimal solutions for the studied friction stir welding process. The optimal solutions are primarily constrained by the lower bound of the temperature. The lower this lower bound temperature is the higher travel speed can go. The linear surrogate model results in a slightly better optimal solution than the non-linear model when the temperature constraint is loose and the converse is true when the temperature constraint is tight. Comparing all five metaheuristics, differential evolution has the best performance, followed by particle swarm optimisation, ant colony optimisation, genetic algorithm, and lastly harmony search.