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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
Conference Dates
June 12-16, 2023
Conference Location
New Brunswick, NJ, US
Conference Title
2023 MSEC Manufacturing Science & Engineering Conference

Keywords

AM Process Control, Digital Twins, Time-stepped digital command

Citation

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 June 19, 2024)

Issues

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Created September 28, 2023, Updated January 23, 2024