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Digital twins : an analysis framework and open issues
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Boyes, Hugh and Watson, Tim (2022) Digital twins : an analysis framework and open issues. Computers in Industry, 143 . 103763. doi:10.1016/j.compind.2022.103763 ISSN 2049-4297.
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Official URL: http://dx.doi.org/10.1016/j.compind.2022.103763
Abstract
The concept of twinning an operational physical system with a functional replica is not new, having been practiced in the space sector for over 50 years. Advances in digitalisation have created opportunities to extract data, obtain insights and achieve greater situational awareness of a physical system’s performance. Increasing interest in the concept has led to a proliferation of digital twin definitions, which are used to frame discussions about specific digital twins. Consequentially comparison of the capabilities of specific digital twins is difficult as they are analysed using different definitions. This paper proposes an analysis framework that enables the characteristics of all digital twins to be matched to this framework. Using this framework, a digital twin may be characterised, or two or more digital twins may be compared. By establishing a framework that contains common functional characteristics, we aim to reduce the confusion caused by the plethora of digital twin definitions and their interpretation by suppliers. By focusing only on functionality and not addressing non-functional requirements the analysis allows comparison of different physical and logical instantiations of digital twins.
Item Type: | Journal Article | ||||||||
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Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TS Manufactures |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
Library of Congress Subject Headings (LCSH): | Artificial intelligence -- Industrial applications, Smart structures , Industry 4.0 -- Computer simulation, Manufacturing processes -- Computer simulation | ||||||||
Journal or Publication Title: | Computers in Industry | ||||||||
Publisher: | Elsevier BV | ||||||||
ISSN: | 2049-4297 | ||||||||
Official Date: | December 2022 | ||||||||
Dates: |
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Volume: | 143 | ||||||||
Article Number: | 103763 | ||||||||
DOI: | 10.1016/j.compind.2022.103763 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 22 August 2022 | ||||||||
Date of first compliant Open Access: | 22 August 2022 | ||||||||
RIOXX Funder/Project Grant: |
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