Application of the Fog Computing Paradigm to Additive Manufacturing Process Monitoring and Control
Muhammad Adnan, Yan Lu, Albert T. Jones, Fan Tien Cheng
Monitoring and controlling Additive Manufacturing (AM) processes play a critical role in enabling the production of quality parts. Different from the traditional manufacturing processes, 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.
August 12-15, 2019
Austin, TX, US
Solid Freeform Fabrication Symposium 2019
Additive Manufacturing, Fog Computing, Monitoring & Control, Functional Architecture, Control Architecture, Data Analytics.
, Lu, Y.
, Jones, A.
and Cheng, F.
Application of the Fog Computing Paradigm to Additive Manufacturing Process Monitoring and Control, Solid Freeform Fabrication Symposium 2019, Austin, TX, US
(Accessed October 17, 2021)