Cognitive digital twin: an approach to improve the maintenance management

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dc.contributor.authorD’Amico, Rosario Davide
dc.contributor.authorErkoyuncu, John Ahmet
dc.contributor.authorAddepalli, Sri
dc.contributor.authorPenver, Steve
dc.date.accessioned2022-06-30T11:07:05Z
dc.date.available2022-06-30T11:07:05Z
dc.date.issued2022-06-23
dc.description.abstractDigital twin (DT) technology allows the user to monitor the asset, specifically over the operation and service phase of the life cycle, which is the longest-lasting phase for complex engineering assets. This paper aims to present a thematic review of DTs in terms of the technology used, applications, and limitations specifically in the context of maintenance. This review includes a systematic literature review of 59 articles on semantic digital twins in the maintenance context. Key performance indicators and explanations of the main concepts constituting the DT have been presented. This article contains a description of the evolution of DTs together with their characterisation for maintenance purposes. It provides an ontological approach to develop DT and improve the maintenance management leading to the creation of a structured DT or a Cognitive Twin (CT). Moreover, it points out that using a top-level ontology approach should be the starting point for the creation of CT. Enabling the creation of the digital framework that will break down silos, ensuring a perfect integration in a network of twins’ scenario.en_UK
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC): EP/R032718/1en_UK
dc.identifier.citationD'Amico DR, Erkoyuncu JA, Addepalli S, Penver S. (2022) Cognitive digital twin: an approach to improve the maintenance management, CIRP Journal of Manufacturing Science and Technology, Volume 38, August 2022, pp. 613-630en_UK
dc.identifier.eissn1878-0016
dc.identifier.issn1755-5817
dc.identifier.urihttps://doi.org/10.1016/j.cirpj.2022.06.004
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18106
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectBasic Formal Ontology (BFO)en_UK
dc.subjectCognitive twinen_UK
dc.subjectDigital twinen_UK
dc.subjectOntologyen_UK
dc.subjectPredictive maintenanceen_UK
dc.subjectTop-level ontology (TLO)en_UK
dc.titleCognitive digital twin: an approach to improve the maintenance managementen_UK
dc.typeArticleen_UK

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