Design and implementation of a process optimizer: A case study on monitoring molding operations

H. C.W. Lau, Ka Man Lee, W. H. Ip, Tung Sun Chan, R. W.K. Leung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)

Abstract

To cope with the requirements of high dimensional accuracy for injection molding components, it is important to optimize the process parameters in order to sustain the high level dimensional quality of the molded parts. In this respect, a study in the domain of process optimization is of paramount importance in terms of determining the optimal set of injection molding parameters. To this end, a methodology to establish an integrated model which consists of both fuzzy logic reasoning and a genetic algorithm is proposed. These two artificial intelligence techniques can complement each other to form an integrated model which capitalizes on the merits and at the same time offsets the pitfalls of the involved technologies. To validate the feasibility of the proposed model, a case study related to injection molding optimization is also covered in this paper.
Original languageEnglish
Pages (from-to)12-21
Number of pages10
JournalExpert Systems
Volume22
Issue number1
DOIs
Publication statusPublished - 1 Jan 2005

Keywords

  • Artificial intelligence
  • Fuzzy logic reasoning
  • Genetic algorithm
  • Optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

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