Engineering Project Health Management: A Computational Approach for Project Management Support Through Analytics of Digital Engineering Activity

Chris Snider, James Gopsill, Simon Jones, Lia Emanuel, Ben Hicks

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    18 Citations (Scopus)
    422 Downloads (Pure)

    Abstract

    Due to the situational and contextual individuality of engineering work, the in-progress monitoring and assessment of those factors that contribute to the success and performance in a given scenario poses a distinct and unresolved challenge, with heavy reliance on managerial skill and interpretation. Termed engineering project health management (EPHM), this paper presents a novel approach and framework for monitoring of engineering work through data-driven and computational analytics that in turn support the managerial interpretation and generation of higher level, context-specific understanding. EPHM is formed through the first adaptation of integrated vehicle health management (IVHM) to the field of engineering management; an approach that has been used to-date for the machine monitoring and predictive maintenance. The approach is applied to four industrial cases, which demonstrates the generation of project-specific information. The approach thereby acts to increase understanding of an engineering activity and a work state, and is complementary to existing managerial toolsets and approaches. A key tenet of the adaption of IVHM is to place the manager in a central role, supporting their professional judgment while reducing investigative effort.

    Original languageEnglish
    Number of pages12
    JournalIEEE Transactions on Engineering Management
    Early online date12 Jul 2018
    DOIs
    Publication statusE-pub ahead of print - 12 Jul 2018

    Keywords

    • Complexity theory
    • Decision making
    • Engineering management
    • integrated vehicle health management (IVHM)
    • Maintenance engineering
    • Monitoring
    • process monitoring and control
    • Project management
    • project management
    • project performance
    • project success factors
    • Research and development management
    • Task analysis

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    • LOCM: The Language of Collaborative Manufacturing

      Gopsill, J. A. (Researcher), McAlpine, H. C. (Manager), McMahon, C. A. (Co-Principal Investigator), Snider, C. M. (Researcher), Shi, L. (Researcher), Watts, L. (Co-Principal Investigator), Jones, S. (Researcher), Johnson, P. (Co-Principal Investigator), Newnes, L. (Co-Principal Investigator), Payne, S. (Co-Principal Investigator), Culley, S. (Co-Principal Investigator) & Hicks, B. J. (Principal Investigator)

      1/02/1331/07/18

      Project: Research

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