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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Springer London

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DOI

10.1016/0022-3468(68)90128-0

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ISSN

1433-3058

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An effective system for parameter optimization in

Authors: WenChin Chen XiaoYun Jiang HuiPin Chang HisaPing Chen
Publish Date: 2013/02/23
Volume: 24, Issue: 6, Pages: 1391-1401
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Abstract

In the current thinfilm transistor liquid crystal display industry the light guide plate LGP of the backlight module has become thinner and smaller and the backlight module needs to be illuminated uniformly and effectively The parameter setting for the photolithography process of a LGP stamper often relies on the engineers’ experiences by means of trialanderror or design of experiment to obtain a suitable and more reliable process parameter setting which requires a large amount of time manpower and cost This research proposes a novel twostage optimization system for photolithography process integrating the Taguchi method backpropagation neural networks genetic algorithms particle swarm optimization and related technologies to effectively generate optimal process parameter settings The first stage is to reduce the process variance The second stage is to find the final optimal process parameter settings for the best quality specification Experimental results show that the proposed system can create the best process parameters which not only meet the quality specification for the microdots on the photoresist but also effectively enhance the overall process stabilityThis research was supported by a grant NSC 992221E216034 from the National Science Council Taiwan The authors would like to thank Material and Chemical Research Laboratories of Industrial Technology Research Institute in Taiwan for providing equipment and technical support

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