Multi objective optimization of cellular scanning strategy in selective laser melting
The scanning strategy for selective laser melting an additive manufacturing process determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process induced defects. The goal of this study is to develop a multi objective approach to optimize the cellular scanning strategy such that the two aforementioned defects are minimized. The decision variable in the chosen problem is a combination of the sequence in which cells are processed and one of six scanning strategies applied to each cell. Thus, the problem is a combination of combinatorial and choice optimization, which makes the problem difficult to solve. On a process simulation domain consisting of 32 cells, our multi objective evolutionary method is able to find a set of trade off solutions for the defined conflicting objectives, which cannot be obtained by performing merely a local search. Possible similarities in Pareto optimal solutions are explored.
2017 IEEE Congress on Evolutionary Computation (CEC)