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

Research output: Contribution to journalArticle

Original languageEnglish
Number of pages12
JournalIEEE Transactions on Engineering Management
Early online date12 Jul 2018
DOIs
DateAccepted/In press - 31 May 2018
DateE-pub ahead of print (current) - 12 Jul 2018

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.

    Research areas

  • 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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    Rights statement: This is the final published version of the article (version of record). It first appeared online via IEEE at https://ieeexplore.ieee.org/document/8410593/authors#authors . Please refer to any applicable terms of use of the publisher.

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