Data: A Design Framework for Adaptive Digital Twins

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dc.contributor.authorahmet Erkoyuncu, John
dc.contributor.authorFernández del amo blanco, Iñigo
dc.contributor.authorAriansyah, Dedy
dc.contributor.authorBulka, Dominik
dc.contributor.authorVrabič, Rok
dc.contributor.authorRoy, Rajkumar
dc.date.accessioned2024-06-07T03:32:30Z
dc.date.available2024-06-07T03:32:30Z
dc.date.issued2023-09-04 09:26
dc.description.abstractThis paper develops a new DT design framework that uses ontologies to enable co-evolution with the CES by capturing data in terms of variety, velocity, and volume across the asset life-cycle. The framework has been tested successfully on a helicopter gearbox demonstrator and a mobile robotic system across their life cycles, illustrating DT adaptiveness without the data architecture needing to be modified. The data presented in this portal is related to the data that was generated in the validation process.
dc.description.sponsorshipDigital Toolkit for optimisation of operators and technology in manufacturing partnerships (DigiTOP)
dc.identifier.citationErkoyuncu, John ahmet; Fernández del amo blanco, Iñigo; Ariansyah, Dedy; Bulka, Dominik; Vrabič, Rok; Roy, Rajkumar (2023). Data: A Design Framework for Adaptive Digital Twins. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.12136074
dc.identifier.doi10.17862/cranfield.rd.12136074
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/22085
dc.publisherCranfield University
dc.relation.isreferencedbyhttps://doi.org/10.1016/j.cirp.2020.04.086'
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject'Digital twins'
dc.subject'Design method'
dc.subject'Ontology'
dc.subject'Computer Engineering'
dc.subject'Engineering Practice'
dc.subject'Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)'
dc.titleData: A Design Framework for Adaptive Digital Twins
dc.typeDataset

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