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

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:

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

Acknowledgement

The work described in this paper was supported substantially by a grant from Hong Kong Polytechnic University (project No. G-YE05).