The transmittance estimations of TP film with Cr and Cr2O3 coating

This paper presents the transmittance estimations for touch panel (TP) film with Cr and Cr₂O₃ coating by using neural network (NN) model. The NN model with quasi-Newton learning method was used to obtain the mapping between TP transmittance and its all possible influencing factors. This study tries to develop an artificial intelligent (AI) evaporation decision mechanism which can help the technician to set the related control parameters before the film´s evaporation process is taken. The transmittance is one of important determination factors used for checking whether the quality of TP is qualified or not. Thus, a smart decision mechanism not only can help technician to improve the work efficiency, but also can reduce the running cost of the company due to the defective products.