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

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

Authors

C. K. Kwong

K. Y. Chan

Profile image of Mehmet Aydin

Dr Mehmet Aydin Mehmet.Aydin@uwe.ac.uk
Senior Lecturer in Networks and Mobile Computing

T. C. Fogarty



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.

Journal Article Type Article
Online Publication Date Feb 22, 2007
Publication Date Nov 15, 2006
Deposit Date May 6, 2021
Journal International Journal of Production Research
Print ISSN 0020-7543
Electronic ISSN 1366-588X
Publisher Taylor & Francis
Peer Reviewed Peer Reviewed
Volume 44
Issue 22
Pages 4815-4836
DOI https://doi.org/10.1080/00207540600620880
Public URL https://uwe-repository.worktribe.com/output/6545511