A knowledge management approach for managing uncertainty in manufacturing

S. C.L. Koh, A. Gunasekaran

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74 Scopus citations

Abstract

Purpose This paper proposes a knowledge management approach for managing uncertainty in manufacturing enterprises. Design/methodology/approach The knowledge management approach consists of a knowledge-enriched manufacturing system, which is modelled using SIMAN simulation language and programmed using Visual Basic applications. A knowledge-based planning module and an execution platform are simulated so that signals could be transferred, and configuration to the planned parameters could be made, in order to minimise variations due to uncertainties. A reference architecture and intelligent agent are created to store tacit knowledge and create explicit knowledge, respectively. Findings Manufacturing enterprises should use both tacit knowledge about uncertainties and buffering and dampening techniques, simultaneously with the explicit knowledge that is generated by the intelligent agent, for managing uncertainty. The design of the knowledge management approach enables easy integration with material requirements planning, manufacturing resource planning or enterprise resource planning systems, and complements with the adoption of advanced technology. Originality/value A new concept – management by valued-added urgency, emerges that underpins the knowledge management approach. It is grounded from the previous literature on managing uncertainty classified into: masking approach; standardising approach; prioritising approach; and optimising approach and extended Westbrook's priority management theory. This concept focuses selectively on value-added changes that need to be made to counteract variations caused by significant uncertainty.

Original languageEnglish (US)
Pages (from-to)439-459
Number of pages21
JournalIndustrial Management and Data Systems
Volume106
Issue number4
DOIs
StatePublished - Apr 1 2006

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Industrial relations
  • Computer Science Applications
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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