A design framework for adaptive digital twins
dc.contributor.author | Erkoyuncu, John Ahmet | |
dc.contributor.author | Fernández del Amo, Iñigo | |
dc.contributor.author | Ariansyah, Dedy | |
dc.contributor.author | Bulka, Dominik | |
dc.contributor.author | Vrabič, Rok | |
dc.contributor.author | Roy, Rajkumar | |
dc.date.accessioned | 2020-07-21T08:20:34Z | |
dc.date.available | 2020-07-21T08:20:34Z | |
dc.date.freetoread | 2020-07-21 | |
dc.date.issued | 2020-05-20 | |
dc.description.abstract | Digital Twin (DT) is a ‘living’ entity that offers potential with monitoring and improving functionality of interconnected complex engineering systems (CESs). However, lack of approaches for adaptively connecting the existing brownfield systems and their data limits the use of DTs. This 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. | en_UK |
dc.identifier.citation | Erkoyuncu JA, Fernández del Amo I, Ariansyah D, et al., (2020) A design framework for adaptive digital twins. CIRP Annals - Manufacturing Technology, Volume 69, Issue 1, pp. 145-148 | en_UK |
dc.identifier.cris | 26745014 | |
dc.identifier.issn | 0007-8506 | |
dc.identifier.uri | https://doi.org/10.1016/j.cirp.2020.04.086 | |
dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/15573 | |
dc.language.iso | en | en_UK |
dc.publisher | Elsevier | en_UK |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Digital twins | en_UK |
dc.subject | Design method | en_UK |
dc.subject | Ontology | en_UK |
dc.title | A design framework for adaptive digital twins | en_UK |
dc.type | Article | en_UK |
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