An Axiomatic Categorisation Framework for the Dynamic Alignment of Disparate Functions in Cyber-Physical Systems

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Publication date
2019-07Keyword
Cyber Physical SystemInternet of Things
Industry 4.0
Multidisciplinary design
Intelligent Vehicle Healthcare Management
IVHM
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© 2019 The authors. This work is licensed under a Creative Commons Attribution 4.0 International License. http://creativecommons.org/licenses/by/4.0/Peer-Reviewed
YesAccepted for publication
2019-04-04
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Advancing Industry 4.0 concepts by mapping the product of the automotive industry on the spectrum of Cyber Physical Systems, we immediately recognise the convoluted processes involved in the design of new generation vehicles. New technologies developed around the communication core (IoT) enable novel interactions with data. Our framework employs previously untapped data from vehicles in the field for intelligent vehicle health management and knowledge integration into design. Firstly, the concept of an inter-disciplinary artefact is introduced to support the dynamic alignment of disparate functions, so that cyber variables change when physical variables change. Secondly, the axiomatic categorisation (AC) framework simulates functional transformations from artefact to artefact, to monitor and control automotive systems rather than components. Herein, an artefact is defined as a triad of the physical and engineered component, the information processing entity, and communication devices at their interface. Variable changes are modelled using AC, in conjunction with the artefacts, to aggregate functional transformations within the conceptual boundary of a physical system of systems.Version
Accepted manuscriptCitation
Byrne TJ, Doikin A, Campean IF et al (2019) An Axiomatic Categorisation Framework for the Dynamic Alignment of Disparate Functions in Cyber-Physical Systems. Proceedings of The 22nd International Conference on Engineering Design (ICED). 5-8 Aug, Delft, Netherlands. 1(1): 3581-3590.Link to Version of Record
https://doi.org/10.1017/dsi.2019.365Type
Conference paperae974a485f413a2113503eed53cd6c53
https://doi.org/10.1017/dsi.2019.365