The Development of a Training Expert System for TFT-LCD Defects Inspection - Chang, Jung-Jung; Hwang, Sheue-Ling; Wen, Chao-Hua (International Journal of Industrial Engineering: Theory, Applications and Practice, 2022)
At present, the image quality of LCD panels has been determined subjectively by human visual inspection. In fact, the inspectors need to memorize a large number of instructions. The inspection tasks include a series of complicated procedures that increase the workload of the inspectors. This research focuses on the improvement of LCD inspection. The knowledge extracting of inspection data was to analyze association rules through interviewing experienced inspectors. Then the nested IF-THEN inspection rules between defects and test patterns were analyzed by two-dimensional matrix and group technology (GT). In terms of inspection test patterns, the occurring sequence of pattern was rearranged to make inspection tasks more efficient. Furthermore, this study aimed to construct an expert system for LCD defects inspection. According to the results of the experiment and expert evaluation, the expert system was proposed as a training support system to aid the trainees to learn inspection skills more effectively. Therefore, the performance of the inspection training could be improved.