Applications in Data-Driven Additive Manufacturing
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-32154-2_3
Reference260 articles.
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3. X. Yao, S.K. Moon, G. Bi, A hybrid machine learning approach for additive manufacturing design feature recommendation. Rap. Prototyp. J. 23(6), 983–997 (2017)
4. G.X. Gu et al., Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment. Mater. Horiz. 5(5), 939–945 (2018)
5. Y. Yang, M. He, L. Li, A new machine learning based geometry feature extraction approach for energy consumption estimation in mask image projection stereolithography. Proc. CIRP 80, 741–745 (2019)
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