Development of fuzzy clustering engine for decision making in manufacturing

Y. Q. Lv, Ka Man Lee

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This paper proposes a two-stage fuzzy clustering engine by combining fuzzy clustering method and fuzzy inference method. In the first stage, the raw data during manufacturing process can be classified based on its own nature, and with the classification results, operation decision can be made in the second stage by running fuzzy inference engine without relying on highly skilled expert. The objective of the proposed method eliminates the human interference so that the decision can be much more impersonal and reliable. In addition, to improve the performance, fuzzy rules in this engine are mostly derived from the natural feature of the raw data rather than the tradition fuzzy rules formalization. Also, a case study of a company based in Singapore has been presented, and the results are promising and satisfied by the company.
Original languageEnglish
Title of host publication5th IEEE International Conference on Management of Innovation and Technology, ICMIT2010
Pages1002-1007
Number of pages6
DOIs
Publication statusPublished - 30 Jul 2010
Externally publishedYes
Event5th IEEE International Conference on Management of Innovation and Technology, ICMIT2010 - Singapore, Singapore
Duration: 2 Jun 20105 Jun 2010

Conference

Conference5th IEEE International Conference on Management of Innovation and Technology, ICMIT2010
Country/TerritorySingapore
CitySingapore
Period2/06/105/06/10

Keywords

  • Decision making
  • Fuzzy clustering
  • Fuzzy inference

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Strategy and Management

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