Real-time process mining system for supply chain network: OLAP-based fuzzy approach

G. T.S. Ho, H. C.W. Lau, Ka Man Lee, A. W.H. Ip

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)


Currently, companies active in the development of high-tech products have become more and more complex in the age of mass customisation. Not only do they have to focus on improving product quality, but rather on gaining experience to modify the current processes in order to streamline the integrated workflow. A Real-time Process Mining System (R-PMS) is developed to analyse the proposed XML-based process data for discovering the hidden relationships among processes. The new feature of this system is the incorporation of the process mining engine, which is characterised by the combined capabilities of the Online Analytical Processing (OLAP) and Fuzzy Logic (FL), to form a robust framework for highlighting the undesirable process setting and parameters for further improvement in a real-time manner. The simulation results indicated that the OLAP-based fuzzy approach was generally superior to those of conventional methods which offer higher flexibility on production process management with decision support ability. In this paper, the detailed architecture and a case study have been included to demonstrate the feasibility of the proposed system.
Original languageEnglish
Pages (from-to)84-103
Number of pages20
JournalInternational Journal of Enterprise Network Management
Issue number1
Publication statusPublished - 1 Jan 2008


  • fuzzy reasoning
  • OLAP
  • Online Analytical Processing
  • quality enhancement

ASJC Scopus subject areas

  • Business and International Management
  • Management Science and Operations Research
  • Management of Technology and Innovation


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