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

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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.

Keywords: Fluid dispensing; Genetic algorithms; Neural networks; Orthogonal array

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/00207540600620880

Affiliations: 1: Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, PRC 2: Faculty of Business, Computing and Information Management, London South Bank University, 103 Borough Road, London, UK

Publication date: November 15, 2006

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