Research output per year
Research output per year
Chris Snider, James Gopsill, Simon Jones, Lia Emanuel, Ben Hicks
Research output: Contribution to journal › Article (Academic Journal) › peer-review
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 language | English |
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Number of pages | 12 |
Journal | IEEE Transactions on Engineering Management |
Early online date | 12 Jul 2018 |
DOIs | |
Publication status | E-pub ahead of print - 12 Jul 2018 |
Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)
Gopsill, J. A., McAlpine, H. C., McMahon, C. A., Snider, C. M., Shi, L., Watts, L., Jones, S., Johnson, P., Newnes, L., Payne, S., Culley, S. & Hicks, B. J.
1/02/13 → 31/07/18
Project: Research
Person: Academic