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Application of Digital Twins to Laser Powder Bed Fusion Additive Manufacturing Process Control
Published
Author(s)
Ho Yeung, Felix Kim, Alkan Donmez
Abstract
Digital twin for additive manufacturing (AM) has drawn much research attention recently, thanks to the advancement in artificial intelligence and machine learning. Machine learning takes the process and measurement data from the manufacturing process to build data-driven models instead of physics-based descriptive models. The latter are usually hard to obtain for complex AM processes such as laser powder bed fusion. This study proposed a digital twin framework for the laser powder bed fusion AM process control and optimization. The framework is created based on the recently-developed advanced point-wise scan control method. It consists of four components: digital twins of process design, process control, process monitoring, and printed part. Their construction is detailed, and potential applications are demonstrated/discussed
Proceedings Title
Proceedings of the ASME 2023 18th International Manufacturing Science and Engineering Conference (MSEC2023)
June 12-16, 2023, New Brunswick, New Jersey
Yeung, H.
, Kim, F.
and Donmez, A.
(2023),
Application of Digital Twins to Laser Powder Bed Fusion Additive Manufacturing Process Control, Proceedings of the ASME 2023 18th International Manufacturing Science and Engineering Conference (MSEC2023)
June 12-16, 2023, New Brunswick, New Jersey
, New Brunswick, NJ, US, [online], https://doi.org/10.1115/MSEC2023-105627, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936204
(Accessed October 14, 2025)