An intelligent agent-based architecture for resilient digital twins in manufacturing

Vrabič, Rok (author), Erkoyuncu, John (author), Farsi, Maryam (author), Ariansyah, Dedy (author)

Digital twins (DTs) offer the potential for improved understanding of current and future manufacturing processes. This can only be achieved by DTs consistently and accurately representing the real processes. However, the robustness and resilience of the DT itself remain an issue. Accordingly, this paper offers an approach to deal with uncertainty and disruptions, as the DT detects these effectively and self-adapts as needed to maintain representativeness. The paper proposes an intelligent agent-based architecture to improve the robustness (including accuracy of representativeness) and resilience (including timely update) of the DT. The approach is demonstrated on a case of cryogenic secondary manufacturing.

• Language: English
• Keywords: manufacturing systems, digital twin, machine learning
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FS - Faculty of Mechanical Engineering
• Publication status: Published
• Publication version: Author Accepted Manuscript
• Year: 2021
• Number of pages: Str. 349-352
• Numbering: Vol. 70, iss. 1
• PID: 20.500.12556/RUL-130813
• UDC: 658.5:004
• ISSN on article: 0007-8506
• DOI: 10.1016/j.cirp.2021.04.049
• COBISS.SI-ID: 76795907
• Publication date in RUL: 17.09.2021

Record is a part of a journal

• Title: CIRP annals
• Shortened title: CIRP ann.
• Publisher: Technische Rundschau, Hallwag Verlag, Colibri, Elsevier
• ISSN: 0007-8506
• COBISS.SI-ID: 170267

Secondary language

• Language: Slovenian
• Keywords: proizvodni sistemi, digitalni dvojčki, strojno učenje

Projects

• Funder: Other - Other funder or multiple funders
• Funding programme: EPSRC
• Project number: EP/R032718/1
• Name: DigiTOP

• Funder: ARRS - Slovenian Research Agency
• Project number: P2-0270
• Name: Proizvodni sistemi, laserske tehnologije in spajanje materialov