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Implementing transmission of data for digital twins in human-centered cyber-physical systems
KTH, School of Industrial Engineering and Management (ITM), Production engineering, Advanced Maintenance and Production Logistics.ORCID iD: 0000-0003-1878-773x
KTH, School of Industrial Engineering and Management (ITM), Production engineering, Advanced Maintenance and Production Logistics.ORCID iD: 0000-0003-0798-0753
Technische Universität Hamburg.ORCID iD: 0000-0003-4817-0562
KTH, School of Industrial Engineering and Management (ITM), Production engineering, Advanced Maintenance and Production Logistics.ORCID iD: 0000-0001-7935-8811
2023 (English)In: Proceedings 56th CIRP International Conference on Manufacturing Systems 2023, Elsevier BV , 2023, Vol. 120, p. 992-997Conference paper, Published paper (Refereed)
Abstract [en]

This study proposes a model describing the functions and procedures for configuring the transmission of data of Digital Twins (DT) in humancenteredCyber-Physical Systems (CPS). We draw data from two cases including aircraft manufacturing and production logistics and presenttwo contributions. First, we derive a procedure identifying the steps and resources of data processing for DT in human-centered CPS. Second,we propose a systematic procedure for configuring bi-directional data transmission depending on the desired system utilization. These resultscontribute to realizing data processing activities supporting the implementation of DTs for human-centered CPS in manufacturing.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 120, p. 992-997
Keywords [en]
digital twin; human-centered cyber-physical system; production logistics; assembly; industry 5.0
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Engineering and Management
Identifiers
URN: urn:nbn:se:kth:diva-342137DOI: 10.1016/j.procir.2023.09.113Scopus ID: 2-s2.0-85184581792OAI: oai:DiVA.org:kth-342137DiVA, id: diva2:1827549
Conference
56th CIRP International Conference on Manufacturing Systems 2023, 24-26 Oct 2023, Cape Town, South Africa
Projects
Explainable and Learning Production Logistics by Artificial Intelligence (EXPLAIN)
Funder
Vinnova, S5014
Note

QC 20240115

Available from: 2024-01-15 Created: 2024-01-15 Last updated: 2024-02-22Bibliographically approved

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Jeong, YongkukFlores-García, ErikWiktorsson, Magnus

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CiteExportLink to record
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Citation style
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Output format
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