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.

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.

Citation

Kwong, C. K., Chan, K. Y., Aydin, M. E., & Fogarty, T. C. (2006). An orthogonal array based genetic algorithm for developing neural network based process models of fluid dispensing. International Journal of Production Research, 44(22), 4815-4836. https://doi.org/10.1080/00207540600620880

• 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