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

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Abstract

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.
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
PublisherSpringer, Cham
Pages600-610
ISBN (Electronic)9783030016142
ISBN (Print)9783030016135
DOIs
Publication statusPublished - 8 Dec 2018

Publication series

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

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