An intelligent scanning strategy (SmartScan) for improved part quality in multi-laser PBF additive manufacturing

To enable faster production and/or the manufacture of large parts, multi-laser powder bed fusion (PBF) systems are increasingly being adopted in practice. There is also research indicating that multiple lasers could be used to improve processing conditions in PBF. However, parts produced by single-laser and multi-laser PBF are susceptible to residual stress, deformation, and other defects that are strongly associated with non-uniform temperature distribution. The authors, in their prior work, have proposed an intelligent scan sequence optimization approach, called SmartScan, that uses a physics-based thermal model to achieve uniform temperature distribution and reduced residual stress and deformation. However, SmartScan is currently only applicable to single-laser PBF systems, where it is used for optimizing the sequence of scanning features (i.e., repeating units) of a scan pattern (e.g., a stripe or island). This paper generalizes SmartScan to multi-laser systems and shows that the complexity of the resulting solution grows combinatorially as a function of the number of lasers and scanned features, making it computationally inefficient. To address this issue, it proposes a sequential approximation to the combinatorial solution of SmartScan for multi-laser PBF systems resulting in a solution whose complexity grows linearly with the number of features. Through numerical studies, the sequential approximation is shown to substantially improve computational efficiency, compared to the combinatorial approach, without significant loss of optimality. Adopting the sequential solution, simulations and experiments involving laser marking of stainless steel 316 L plates are used to demonstrate the effectiveness of SmartScan in achieving more uniform temperature distribution compared to heuristic scan sequences in multi-laser PBF. As a result, SmartScan yields up to 40% reduction in measured plate deformation compared to the heuristic approaches.