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

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.