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

被引：6
作者：
Kwong, C. K. [1 ]
Chan, K. Y.
Aydin, M. E.
Fogarty, T. C.
机构：
[1] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Kowloon, Hong Kong, Peoples R China
[2] London S Bank Univ, Fac Business Comp & Informat Management, London, England
来源：
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | 2006年 / 44卷 / 22期
关键词：
neural networks; genetic algorithms; orthogonal array; fluid dispensing;
D O I：
10.1080/00207540600620880
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
引用
收藏
页码：4815 / 4836
页数：22
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