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

5 Citations (Scopus)
271 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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