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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.

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