Application of the fog computing paradigm to additive manufacturing process monitoring and control

Muhammad Adnan, Yan Lu, Al Jones, Fan Tien Cheng

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

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 languageEnglish
Pages254-267
Number of pages14
Publication statusPublished - 2019
Event30th Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, SFF 2019 - Austin, United States
Duration: 2019 Aug 122019 Aug 14

Conference

Conference30th Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, SFF 2019
CountryUnited States
CityAustin
Period19-08-1219-08-14

All Science Journal Classification (ASJC) codes

  • Surfaces, Coatings and Films
  • Surfaces and Interfaces

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