An Experimental Design for Processing Parameter Optimization for Cathode Arc Plasma Deposition of ZnO Films

摘要

An experimental design utilizing artificial neural networks (ANNs), the Taguchi method, and the genetic algorithm (GA) is proposed to obtain optimal processing parameters for cathode arc plasma deposition of ZnO thin films on a glass substrate. The Taguchi method's orthogonal array is used to minimize the number of required experiments and to gather the experimental data. An ANN is then used to construct a system model based on the experimental data. Finally, the GA is used to determine the optimal process parameters. The average resistivity obtained from the optimal processing parameters is 3.19 × 10-3 Q-cm and the average transmittance obtained is 86.04%, both of which improve on results obtained using the Taguchi method alone (3.69 × 10-3 Q-cm and 85.41%). This indicates that the proposed design is a viable approach for determining the optimal process parameters.