Application Research Of CSG Casting Product Quality Control Based On Data Mining

With the rapid development of modern iron and steel enterprises, the quality controloccupies an increasingly important position. It is very critical to implement the quality ofcontrol and management for ensuring the quality of the entire production. Traditionalexperience-based performance analysis of product quality has failed to meet the modernenterprises with the development of information technology. Therefore, how to find thefactors that affect steel product quality in the large amounts of data which the enterprise hasaccumulated, to identify issues that yield in the procedure of quality management, as well asto predictive the product quality, has become an important research direction for the qualitymanagement. In this thesis, on the basis of previous studies, we focus on the quality controlbased on the data mining technology for steel product. The research works of this thesis issummarized as follows:(1) According to the development process of enterprise quality management and thedevelopment of iron and steel enterprise quality management, the development situation ofquality management at home and abroad are introduced and analyzed. Besides, the datamining technology is introduced simply. Especially, the data warehouse technology, decisiontree analysis and the corresponding algorithms are summarized.(2) According to the background of Shaogang enterprise, first, the basic situation ofShaogang and the situation of quality data management are introduced. Second, the problemsof quality data management are analyzed. Finally, the measures are taken into account for theproduct quality data management.(3) First of all, the ideas of product quality management and control are introduced basedon data mining for the data of product quality; second, the features of the quality of productare deeply analyzed, then the data description of characteristics of product quality isestablished based on the frame of data mining. In the framework, the process of data miningis given and the software system structure is designed.(4) A quality prediction model is developed for the product data, and a time-series datamining tech is proposed for the application of the dynamic control of product quality in thethesis. On the basis, applying the decision tree method to analysis the influence of processparameters on product quality and to find the knowledge of quality data which hidden in thedata sets. Finally, the knowledge can be as the favorable decision-making reference. (5) Finally, the summary of the thesis is given.