Siemens Digital Factory
Multiscale methodologies for laser powder bed fusion process simulation: challenges and opportunities
The industrialization of laser powder-bed fusion (LPBF) technology can only be enabled if the productivity and repeatability of the process are increased and its associated costs are decreased. Furthermore, the quality of the as-built material needs improving in order for LPBF to establish itself as a production method for end-use products. In this respect, process simulation technologies are promising tools for the prediction of the manufacturing process outcome. In particular, recent research has shown that Finite Element Analysis-based simulation can predict local defects, such as part distortion, residual stress build-up and porosity, as well as local features such as microstructures. These new simulation technologies promise to give manufacturers the opportunity to undertake corrective actions before starting the building process. However, three important challenges remain open:
• LPBF spans a broad range of spatial and temporal scales and is characterized by a complex interaction of multiphysical phenomena (thermal, mechanical, fluid dynamic, thermodynamic). The computational burden becomes unsustainable if all of the involved scales and physical phenomena are to be simulated for real-world components;
• Commercial software has appeared in the market for the prediction of distortion and residual stress. Such solutions rely on a number of approximations, especially the inherent strain method, to partially tackle the multiscale, multiphysics process simulation problem. However, very few studies have been aimed at quantitatively assessing their predictive accuracy using real-world use-cases. This lack of published data, in turn, risks to hinder the rapid industrial uptake of such software tools;
• Even when correct predictions can be achieved via simulation, it is sometimes not economically viable, or even practically impossible, to undertake corrective actions at design, process or post-process level. Hence, there is a need for software solutions also capable of predicting the effect of the process-induced defects on the operational performance of the printed component.
Research at Siemens Industry Software is being undertaken to develop and validate a number of simulation solutions aimed at predicting the effect of the LPBF process on the build quality and on the operational performance of the built component. The aim of this talk is thus to present some of the most exciting achievements and the most pressing challenges of this research. By means of a number of use-case studies, we show that multiscale modelling can achieve quantitative predictions while maintaining the computational cost of the simulations to a level that is acceptable for modern personal computers.
Michele Garibaldi is a Senior Research and Technology Development Engineer at Siemens Industry Software in Leuven, Belgium. Michele was awarded a PhD in Mechanical Engineering from the University of Nottingham in 2018 for his dissertation on the use of laser Additive Manufacturing to produce soft magnetic materials and its impact on the design of electrical machines. In his role at Siemens Industry Software Michele contributes to the development and validation of simulation methodologies aimed at predicting the outcome of metal additive manufacturing processes at different spatial scales, including the component, melt-pool and microstructural levels. The effect of process-induced defects and microstructural features on the performance of structurally-loaded parts is also a focus point of Michele’s research at Siemens. Michele works as part of a multidisciplinary, international team that has created Siemens’ first AM process simulation solution, Simcenter 3D AM, which is now fully integrated into Siemens’s end-to-end Additive Manufacturing solution in NX.
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