An orthogonal array based genetic algorithm for developing neural network based process models of fluid dispensing

Chun Kit Kwong, K. Y. Chan, M. E. Aydin, T. C. Fogarty

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

Fluid dispensing is a popular process in the semiconductor manufacturing industry, commonly being used in die-bonding as well as microchip encapsulation of electronic packaging. Modelling the fluid dispensing process is important to understanding the process behaviour as well as determining the optimum operating conditions of the process for a high-yield, low-cost and robust operation. In this paper, an approach to integrating neural networks with a modified genetic algorithm is presented to model the fluid dispensing process for electronic packaging. The modified genetic algorithm is proposed by incorporating the crossover operator with an orthogonal array. We compare the modified genetic algorithm with the standard genetic algorithm. The results indicate that a better quality encapsulation can be obtained based on the modified genetic algorithm.
Original languageEnglish
Pages (from-to)4815-4836
Number of pages22
JournalInternational Journal of Production Research
Volume44
Issue number22
DOIs
Publication statusPublished - 15 Nov 2006

Keywords

  • Fluid dispensing
  • Genetic algorithms
  • Neural networks
  • Orthogonal array

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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