Laser Powder Bed Fusion
Laser Powder Bed Fusion (LPBF) is an additive manufacturing technique aiming to create high-quality metal parts by selectively melting powdered metal using a laser. Current research heavily focuses on improving process monitoring and control through in-situ imaging and data-driven models, employing deep learning architectures like U-Nets, diffusion models, and graph neural networks to predict melt pool behavior, detect defects (e.g., pores, overheating), and optimize process parameters for desired material properties. These advancements are crucial for enhancing the reliability, efficiency, and overall quality of LPBF, leading to wider adoption in various industries.
Papers
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