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Model construction and parameter effect for TFT-LCD process based on yield analysis by using ANNs and stepwise regression

机译:基于人工神经网络的产量分析和逐步回归的TFT-LCD工艺模型构建和参数效果

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摘要

The ability to improve yield in manufacturing process is an important competitiveness determinant for TFT-LCD factories. Until now, no any suitable theories were proposed to address the yield problem in TFT-LCD industry. However, the information (e.g. the domain knowledge or the parameter effect) obtained from the yield model will provide useful recommendations and improvements to those manufacturers. That is, the model construction and parameter effect for yield analysis will be a necessary issue to be addressed. In this study, we proposed a procedure incorporating the artificial neural networks (ANNs) and stepwise regression techniques to achieve the model construction and parameter effect. Besides, an illustrative case owing to TFT-LCD manufacturer at Tainan Science Park in Taiwan will be applied to verifying our proposed procedure.
机译:制造过程中提高产量的能力是TFT-LCD工厂重要的竞争力决定因素。迄今为止,尚未提出任何合适的理论来解决TFT-LCD工业中的成品率问题。但是,从产量模型获得的信息(例如领域知识或参数效果)将为这些制造商提供有用的建议和改进。也就是说,用于产量分析的模型构建和参数效果将是需要解决的必要问题。在这项研究中,我们提出了一种程序,该程序结合了人工神经网络(ANN)和逐步回归技术,以实现模型构建和参数效果。此外,将以台湾台南科学园区TFT-LCD制造商的案例为例来验证我们提出的程序。

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