Residual stresses and deformations continue to remain one of the primary challenges towards expanding the scope of selective laser melting as an industrial scale manufacturing process. While process monitoring and feedback-based process control of the process has shown significant potential, there is still dearth of techniques to tackle the issue. Numerical modelling of selective laser melting process has thus been an active area of research in the last few years. However, large computational resource requirements have slowed the usage of these models for optimizing the process.
In this paper, a calibrated, fast, multiscale thermal model coupled with a 3D finite element mechanical model is used to simulate residual stress formation and deformations during selective laser melting. The resulting reduction in thermal model computation time allows evolutionary algorithm-based optimization of the process. A multilevel optimization strategy is adopted using a customized genetic algorithm developed for optimizing cellular scanning strategy for selective laser melting, with an objective of reducing residual stresses and deformations. The resulting thermo-mechanically optimized cellular scanning strategies are compared with standard scanning strategies and have been used to manufacture standard samples.