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    Automotive IVHM: Towards Intelligent Personalised Systems Healthcare

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    automotive_ivhm_towards_intelligent_personalised_systems_healthcare.pdf (1.166Mb)
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    Publication date
    2019
    Author
    Campean, I. Felician
    Neagu, Daniel
    Doikin, Aleksandr
    Soleimani, Morteza
    Byrne, Thomas J.
    Sherratt, A.
    Keyword
    Large-scale engineering systems
    Digital engineering value chains
    Digitised engineering value chains
    Product Lifecycle Management
    PLM
    Integrated Vehicle Health Management
    IVHM
    Digital twin
    Rights
    © 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
    Yes
    
    Metadata
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    Abstract
    Underpinned by a contemporary view of automotive systems as cyber-physical systems, characterised by progressively open architectures increasingly defined by their interaction with the users and the smart environment, this paper provides a critical and up-to-date review of automotive Integrated Vehicle Health Management (IVHM) systems. The paper discusses the challenges with prognostics and intelligent health management of automotive systems, and proposes a high-level framework, referred to as the Automotive Healthcare Analytic Factory, to systematically collect and process heterogeneous data from across the product lifecycle, towards actionable insight for personalised healthcare of systems.
    URI
    http://hdl.handle.net/10454/17013
    Version
    Published version
    Citation
    Campean IF, Neagu D, Doikin A et al (2019) Automotive IVHM: Towards Intelligent Personalised Systems Healthcare. Proceedings of The 22nd International Conference on Engineering Design (ICED 19). 5-8 Aug, Delft, Netherlands. 1(1): 857-866.
    Link to publisher’s version
    https://doi.org/10.1017/dsi.2019.90
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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