This conference paper was submitted for presentation at the NAFEMS World Congress 2025, held in Salzburg, Austria from May 19–22, 2025.

Abstract

Metal 3D printing processes, such as Selective Laser Melting (SLM) and Electron Beam Melting (EBM), exhibit unique characteristics due to their rapid solidification rates, high cooling rates, and localized heat accumulation during layer-by-layer fabrication. These extreme thermal gradients contribute to the formation of complex and heterogeneous microstructures, including cellular dendritic structures, varying grain sizes, and textures, leading to anisotropic and localized variations in mechanical properties. Such microstructural complexities pose significant challenges to the analytical validation and predictive modeling of parts manufactured through 3D printing, particularly in critical applications like the automotive industry, where reliability, safety, and high performance are paramount. To address these challenges, this study utilizes a crystal plasticity finite element method (CPFEM) to predict the mechanical properties of metal 3D-printed components with greater accuracy. The CPFEM model incorporates distinct microstructural features formed during the metal 3D printing process, such as the cellular structures, grain boundary characteristics, and crystallographic textures, directly into the crystal plasticity framework. By doing so, the model captures the anisotropic mechanical behavior and localized property variations inherent in 3D-printed metals, which are often overlooked in conventional finite element analyses that assume homogenous material properties. The computational framework developed in this research includes detailed characterization of the microstructure using advanced imaging techniques, such as electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM), to inform the CPFEM simulations. The model is validated against experimental mechanical testing data, including tensile tests and hardness measurements, to ensure its predictive capability. The findings of this research highlight the significant potential of CPFEM in bridging the gap between the microstructural complexities of 3D-printed materials and their macroscopic mechanical behavior. This approach is particularly relevant for automotive applications, where understanding the mechanical anisotropy, residual stresses, and localized property variations is essential for optimizing the design, performance, and longevity of critical components. By providing a robust and comprehensive methodology for numerical analysis, this study contributes to advancing the use of metal additive manufacturing in the automotive industry. It enables the development of reliable, high-performance parts that are tailored to specific requirements, ultimately pushing the boundaries of design possibilities and contributing to lighter, more efficient vehicles.