Engineering Project Health Monitoring: Application of automatic, real-time analytics to PDM systems

Modern engineering work, both project-based and operations, is replete with complexity and variety making the effective development of detailed understand-ing of work underway difficult, which in turn impacts on management and assur-ance of performance.
Leveraging the digital nature of modern engineering work, recent research has demonstrated the capability and opportunity for implementation of broad-spectrum data analytics for development of detailed management information. Of key benefit is that these analytics may be both real-time and automatic.
This paper contextualises such analytics with respect to PDM through explo-ration of the potential for driving the analytics directly from data typically cap-tured within PDM systems. Through review of twenty-five analytics generated from engineering-based digital assets, this paper examines the subset that may be applied to PDM-driven analysis on systems as-is, examines the coverage of such analytics from the perspective of the potential managerial information and under-standing that could be inferred, and explores the potential for maximizing the set of analytics driven from PDM systems through capture of a minimal set of sup-plementary data. This paper presents the opportunity for integration of detailed analytics of engineering work into PDM systems and the extension of their capa-bility to support project management and team performance.