Using Data Mining Technology to Deign an Quality Control System for Manufacturing Industry

This paper is a quality control system involved in using data mining to discover the main inconsistency reasons in the manufacturing process of semiconductor plants and compare the correctness of classification analysis of the two methods, so as to set up a quality control system providing an efficiency tool for analyzing problems, with a view to identifying the causes of problems, making decision immediately, and eventually reducing the cycle time taken to solve quality-related problems. The contributions of this paper are as follows. Predictions made by decision tree analysis, indicating that decision tree analysis is an effective mean of classification analysis in semiconductor quality problems, whereas evaluation of feasible methods by data mining followed by establishment of the basis for a quality analysis system environment, that is characteristic of knowledge sharing may be applied to analysis of the quality problems in all corporation.