Research Of Data Mining Applied To Quality Management Of Equipment Manufacturing Industry

With the accelerating pace of world economic integration, the market competition is becoming more and more fierce. The equitment manufacturing enterprises should not only to meet the clients’needs, such as product customization, variety, small batch and short delivery, but also to satisfy the requirements of high quality products.The current market competition has shifted from "price competition" to "quality competiton", and the product quality is subject to the survival and development of the enterprises. With this, the advanced quality management has been an important part to improve the core competitive ability for the enterprises. Thus, how to effectively manage and use the large amount of complicated quality data, which generated from the enterprises production and operation, is an urgent problem to be solved.In traditional management mode, a lot of equitment manufacturing enterprises are still limited to the indepent activity of quality supervision departments, which focus on the sub-process for the quality problem. With this, it is hard to control the overall quality level for the production. On the other hand, as the manufacturing informationization develops, the large amount of complicated data which collcetd from the daily production activity are not fully used by the enterprises. And these data are just dealt with simple statistics and diplayed in the form of chart. At the same time, they are lack of a powerful data analysis tool to dig out the useful information which hidden behind the data.According to the status and demands of the quality management for the equitment manufacturing enterprises, this thesis combined the quality mangement technology with the data mining technoly to make full use of the large amount of production data. On this purpose, it can dig out the useful information that it can help to impove the production quality and reduce the unqulified rate. In this thesis, the works can be divided into the following four parts. Firstly, the research background was introduced in this thesis, and the existing problems of the enterprise quality management were also illustrated. Secondly, the technology of data mining and its application feasibility in quality management for equitment manufacturing enterprises were studied at the same time. Thirdly, the technology of data mining was applied in these aspects respectively, such as supplier quality management and quality analysis of production process, to establish the supplier quality evaluation model on the basis of the Apriori association rule algorithm and the process quality analysis model based on the C4.5decision tree algorithm respectively. With this, the useful information and suggestion were proposed from the analysis results to help the enterprises make decision effectively. Lastly, a summary of work in this thesis was made and the future work was also expected.