Daniele Scrimieri
An integrated data- and capability-driven approach to the reconfiguration of agent-based production systems
Scrimieri, Daniele; Adalat, Omar; Afazov, Shukri; Ratchev, Svetan
Authors
Omar Adalat
Shukri Afazov
Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
Cripps Professor of Production Engineering & Head of Research Division
Abstract
Industry 4.0 promotes highly automated mechanisms for setting up and operating flexible manufacturing systems, using distributed control and data-driven machine intelligence. This paper presents an approach to reconfiguring distributed production systems based on complex product requirements, combining the capabilities of the available production resources. A method for both checking the “realisability” of a product by matching required operations and capabilities, and adapting resources is introduced. The reconfiguration is handled by a multi-agent system, which reflects the distributed nature of the production system and provides an intelligent interface to the user. This is all integrated with a self-adaptation technique for learning how to improve the performance of the production system as part of a reconfiguration. This technique is based on a machine learning algorithm that generalises from past experience on adjustments. The mechanisms of the proposed approach have been evaluated on a distributed robotic manufacturing system, demonstrating their efficacy. Nevertheless, the approach is general and it can be applied to other scenarios.
Citation
Scrimieri, D., Adalat, O., Afazov, S., & Ratchev, S. (2022). An integrated data- and capability-driven approach to the reconfiguration of agent-based production systems. International Journal of Advanced Manufacturing Technology, 124(3-4), 1155-1168. https://doi.org/10.1007/s00170-022-10553-0
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 15, 2022 |
Online Publication Date | Nov 29, 2022 |
Publication Date | Dec 29, 2022 |
Deposit Date | Feb 2, 2023 |
Publicly Available Date | Feb 2, 2023 |
Journal | The International Journal of Advanced Manufacturing Technology |
Print ISSN | 0268-3768 |
Electronic ISSN | 1433-3015 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 124 |
Issue | 3-4 |
Pages | 1155-1168 |
DOI | https://doi.org/10.1007/s00170-022-10553-0 |
Keywords | Original Article, Reconfiguration, Capabilities, Multi-agent systems, Machine learning, Assembly |
Public URL | https://nottingham-repository.worktribe.com/output/15923883 |
Publisher URL | https://link.springer.com/article/10.1007/s00170-022-10553-0 |
Additional Information | Received: 21 September 2022; Accepted: 15 November 2022; First Online: 29 November 2022; The authors declare no competing interests. |
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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