Identifying and Visualising KPIs for Collaborative Engineering Projects: a Knowledge Based Approach

Lei Shi, Linda B Newnes, Steve Culley, James A Gopsill, Simon L Jones, Chris Snider

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

5 Citations (Scopus)
107 Downloads (Pure)

Abstract

Nowadays manufacturing involves high volume of complex operational processes, distributed resources and international/intersectional collaborations, which cause the evaluation of performance for related engineering projects to become a challenge. The performance of project is a key factor that determines the quality of output, and its temporal changes could reflect the status of project execution at current time, as well as indicate the potential issues for the near future. As a result, monitoring the change of performance is an essential approach to ensure the project execution is on track. It could raise awareness of project participants upon any issue occurs, and enable them to make appropriate decisions on a real-time basis.

To facilitate the evaluation of project performance in collaborative environments, this research aims to propose an automatic approach to extracting key performance indicators (KPIs) from project related data, and also to demonstrate how the domain knowledge can facilitate the process of KPIs identification and visualisation.
Original languageEnglish
Title of host publicationDS 80-3 Proceedings of the 20th International Conference on Engineering Design (ICED 15) Vol 3
Subtitle of host publicationOrganisation and Management, Milan, Italy, 27-30.07.15
EditorsChristian Weber, Stephan Husung, Marco Cantamessa, Gaetano Cascini, Dorian Marjanovic, Francesca Montagna
PublisherThe Design Society
Pages377-386
Number of pages10
Volume3
ISBN (Print)9781904670667
Publication statusPublished - 27 Jul 2015

Publication series

NameProceedings of the International Conference on Engineering Design (ICED)
PublisherThe Design Society
Number3
Volume80
ISSN (Print)2220-4334

Keywords

  • Complexity
  • Decision making
  • Knowledge management
  • Visualisation

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