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Semantic models and knowledge graphs as manufacturing system reconfiguration enablers

Mo, Fan; Chaplin, Jack C.; Sanderson, David; Martínez-Arellano, Giovanna; Ratchev, Svetan

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Authors

Fan Mo

Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
Cripps Professor of Production Engineering & Head of Research Division



Contributors

Fan Mo
Researcher

Abstract

Reconfigurable Manufacturing System (RMS) provides a cost-effective approach for manufacturers to adapt to fluctuating market demands by reconfiguring assets through automated analysis of asset utilization and resource allocation. Achieving this automation necessitates a clear understanding, formalization, and documentation of asset capabilities and capacity utilization. This paper introduces a unified model employing semantic modeling to delineate the manufacturing sector's capabilities, capacity, and reconfiguration potential. The model illustrates the integration of these three components to facilitate efficient system reconfiguration. Additionally, semantic modeling allows for the capture of historical experiences, thus enhancing long-term system reconfiguration through a knowledge graph. Two use cases are presented: capability matching and reconfiguration solution recommendation based on the proposed model. A thorough explication of the methodology and outcomes is provided, underscoring the advantages of this approach in terms of heightened efficiency, diminished costs, and augmented productivity.

Citation

Mo, F., Chaplin, J. C., Sanderson, D., Martínez-Arellano, G., & Ratchev, S. (2024). Semantic models and knowledge graphs as manufacturing system reconfiguration enablers. Robotics and Computer-Integrated Manufacturing, 86, Article 102625. https://doi.org/10.1016/j.rcim.2023.102625

Journal Article Type Article
Acceptance Date Jul 19, 2023
Online Publication Date Sep 8, 2023
Publication Date 2024-04
Deposit Date Sep 28, 2023
Publicly Available Date Sep 28, 2023
Journal Robotics and Computer-Integrated Manufacturing
Print ISSN 0736-5845
Electronic ISSN 1879-2537
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 86
Article Number 102625
DOI https://doi.org/10.1016/j.rcim.2023.102625
Keywords Semantic models; Knowledge graphs; Reconfigurable manufacturing systems; Capability matching
Public URL https://nottingham-repository.worktribe.com/output/25383246
Publisher URL https://www.sciencedirect.com/science/article/pii/S073658452300100X?via%3Dihub
Additional Information This article is maintained by: Elsevier; Article Title: Semantic models and knowledge graphs as manufacturing system reconfiguration enablers; Journal Title: Robotics and Computer-Integrated Manufacturing; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.rcim.2023.102625; Content Type: article; Copyright: © 2023 The Author(s). Published by Elsevier Ltd.

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