Skip to content

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationProduct Lifecycle Management to Support Industry 4.0
Subtitle of host publication15th IFIP WG 5.1 International Conference, PLM 2018, Turin, Italy, July 2-4, 2018, Proceedings
Publisher or commissioning bodySpringer, Cham
ISBN (Electronic)9783030016142
ISBN (Print)9783030016135
DateAccepted/In press - 1 May 2018
DatePublished (current) - 8 Dec 2018

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer Link
ISSN (Print)1868-4238


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.

Download statistics

No data available



  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the accepted author manuscript (AAM). The final published version (version of record) is available online via Springer Link at . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 201 KB, PDF document

    Licence: Other


View research connections

Related faculties, schools or groups