Data Analytics and Machine Learning in Metal Additive Manufacturing—Challenges, Segmentations, and Applications
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Published:2023
Abstract
This article presents the analytics challenges in additive manufacturing. It discusses the types and applications of data analytics. Data analytics can be classified into four types: descriptive, diagnostic, predictive, and prescriptive. The diverse applications of data analytics and machine learning include design, process-structure-properties (PSP) relationships, and process monitoring and quality control. The article also presents tools used for data analytics.
Alex Kitt, Hyunwoong Ko, Data Analytics and Machine Learning in Metal Additive Manufacturing—Challenges, Segmentations, and Applications, Additive Manufacturing Design and Applications, Vol 24A, ASM Handbook, Edited By Mohsen Seifi, David L. Bourell, William Frazier, Howard Kuhn, ASM International, 2023, p 177–183, https://doi.org/10.31399/asm.hb.v24A.a0006975
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