Multi‐objective Bayesian modeling and optimization of 3D printing process via experimental data‐driven method
Chunfeng Ding,
Jianjun Wang,
Yan Ma
et al.
Abstract:The instability of product quality and low printing efficiency are the main obstacles to the widespread application of 3D printing in the manufacturing industry. Optimizing printing parameters can substantially improve product quality and printing efficiency. However, existing methods for optimizing process parameters primarily rely on computationally expensive numerical simulations or costly physical experiments, which cannot balance model accuracy and experiment cost. To the best of our knowledge, almost no … Show more
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