Abstract
Monitoring and controlling Additive Manufacturing (AM) processes play a critical role in enabling the production of quality parts. AM processes generate large volumes of structured and unstructured in-situ measurement data. The ability to analyze this volume and variety of data in real-time is necessary for effective closed-loop control and decision-making. Existing control architectures are unable to handle this level of data volume and speed. This paper investigates the functional and computational requirements for real-time closed-loop AM process control. The paper uses those requirements to propose a function architecture for AM process monitoring and control. That architecture leads to a fog-computing solution to address the big data and real-time control challenges.
Original language | English |
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Pages | 254-267 |
Number of pages | 14 |
Publication status | Published - 2019 |
Event | 30th Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, SFF 2019 - Austin, United States Duration: 2019 Aug 12 → 2019 Aug 14 |
Conference
Conference | 30th Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, SFF 2019 |
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Country/Territory | United States |
City | Austin |
Period | 19-08-12 → 19-08-14 |
All Science Journal Classification (ASJC) codes
- Surfaces, Coatings and Films
- Surfaces and Interfaces