Abstract
Power metallurgy hot isostatic pressing (PM-HIP) is a manufacturing technique capable of producing net shape or near-net shape components with complicated geometries from materials that are difficult to melt and cast, mechanically deform or weld. However, the process and soundness of the outcome are extremely sensitive to the geometric design of the capsule (also known as the die or can) that is used in the process. The capsule design for each new component involves several trial–error iterations to achieve the desired geometry and shape of the component. For each iteration, costly HIP experiments need to be conducted and new capsules need be manufactured with small modifications. In this study, a robust finite element analysis (FEA) model of the HIP process is developed, then wrapped in a multi-objective genetic algorithm (MOGA) optimization framework to obtain the optimal pre-HIP capsule design, which yields the desired post-HIP component geometry in one HIP run. The FEA-based optimization algorithm is validated by HIP experiments, showing excellent agreement between the experiment and the model.
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