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Title: |
Optimization of Photolithography Process for a LGP Molding Stamper |
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Source: |
International Conference on Engineering and Business Management (EBM 2010 PAPERBACK)
(pp 4626-4629)
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Author(s): |
Wen-Chin CHEN, Department of Industrial Management, Chung Hua University, Hsinchu, Chinese Taipei
His-Ping CHEN, Department of Industrial Management, Chung Hua University, Hsinchu, Chinese Taipei ;Industrial technology research institute, Hsinchu, Chinese Taipei
Xing-Hua CHEN, Industrial technology research institute, Hsinchu, Chinese Taipei |
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Abstract: |
Abstract: This study focuses on optimization of the photolithography process for a light guide plate molding (LGP) stamper. Taguchi method, the back-propagation neural networks (BPNN) and genetic algorithms (GA) was used to develop a photolithography process optimization system. In the first phase of this study, Taguchi orthogonal array was employed to arrange the experimental work, to calculate the S/N ratio, and to determine the initial process parameter settings. The control factors are heaters temperature, heaters time, roller temperature, exposure energy, and development speed. We conduct Taguchi orthogonal table experiments to identify the quality characteristics meet the objectives of process parameter combination. In the second phase, Taguchi experimental data were employed to build BPNN quality predictor, and then we used ANOVA analysis to select control factors. Finally, the quality predictor was combined with GA to find the best combination of process parameters. The experimental results showed that the best parameter combination effectively control the quality, stability and cost savings.
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