Predicting defects in SLM-produced parts based on melt pools clustering analysis
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00170-024-14134-1.pdf
Reference41 articles.
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3. Gunasegaram D, Barnard A, Matthews M, Jared B, Andreaco A, Bartsch K, Murphy A (2024) Machine learning-assisted in-situ adaptive strategies for the control of defects and anomalies in metal additive manufacturing. Addit Manuf, 104013
4. Xames MD, Torsha FK, Sarwar F (2023) A systematic literature review on recent trends of machine learning applications in additive manufacturing. J Intell Manuf 34(6):2529–2555
5. Zhao Z, Liu W, Ren J, Wang C, He Y, Zhang X, Chen X (2024) Uncertainty driven trustworthy defect detection for high resolution powder bed images in selective laser melting. J Manuf Syst 72:59–73
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