Additive manufacturing (AM) technology is becoming more popular for the fabrication of 3D metal products as it offers rapid prototyping and large design freedom. However, part quality and fatigue performance of components fabricated by current AM technology are not comparable to that produced by traditional methods. Post-build processing techniques, such as heat treatment (HT) and Hot Iso-static Pressing (HIP), have been developed to improve microstructure and remove internal flaws that are detrimental to fatigue resistance. In order to simulate the HT and HIP process and optimize the post-build process, an integrated computational materials engineering (ICME) approach is utilized to link the process parameters with material’s structures, properties, and fatigue performance. The purpose of this study is two-fold. First, we simulate the HT/HIP process including the physics of heat transfer, and porosity evolution. Second, a state-of-the-art hybrid optimization approach, combining response surface method and genetic algorithm is utilized to optimize the post-build process parameters in order to minimize porosities.

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