Determination of process conditions of epoxy dispensing processes using a genetic algorithm based neural fuzzy networks

K. Y. Chan, T. S. Dillon, S. H. Ling, Chun Kit Kwong

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

2 Citations (Scopus)

Abstract

In this paper, process conditions of epoxy dispensing processes are determined by the proposed genetic algorithm based neural fuzzy networks, which consists of two tasks: a) the approach of neural fuzzy networks, which was shown to be better than the other existing approaches, is proposed to develop models in relating between process parameters and quality characteristics for the epoxy dispensing processes; b) the approach of genetic algorithm is used to determine process parameters with respect to pre-defined quality requirements based on the developed neural fuzzy network models. The results indicate that, based on the proposed genetic algorithm based neural fuzzy network, estimated process parameters can achieve specified requirements of microchip encapsulations with high and robust qualities.
Original languageEnglish
Title of host publicationFUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
Pages2253-2260
Number of pages8
DOIs
Publication statusPublished - 27 Sep 2011
Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
Duration: 27 Jun 201130 Jun 2011

Conference

Conference2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
Country/TerritoryTaiwan
CityTaipei
Period27/06/1130/06/11

Keywords

  • Epoxy dispensing process
  • microchip encapsulation
  • neural fuzzy networks

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Applied Mathematics
  • Theoretical Computer Science

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