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Application Research On Data Mining Technology Of Quality Control In Building Material Equipment Manufacturing Process

Posted on:2016-06-12Degree:MasterType:Thesis
Country:ChinaCandidate:Z B WangFull Text:PDF
GTID:2348330476955453Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
As Product quality plays a decisive role in the competition between the enterprises, it is very important to take control of the manufacturing process quality for the enterprises in order to guarantee the quality of the product. In general, a large amount of original quality data are accumulated during the manufacturing process of products, but traditional statistical methods have been unable to carry on the better guidance to the quality. So, how to find the key factors that affecting the quality from a large amount of data and given the decision-making method to ensure the quality of the manufacturing process of continuous improvement, has become an urgent need to solve the problem of the building materials and equipment enterprises. Based on this, this paper mainly takes the building material equipment manufacturing enterprise as the research object and carries out the research on data mining technology of quality control in building material equipment manufacturing process. The main research contents including:(1) Analyzed the Development present situation of building materials equipment manufacturing enterprises, and made a simple introduction for the development status and application of data mining technology. Meanwhile, analyzed the Research Status of neural network and rough set technology and carried on the problem description for process quality control of building materials equipment manufacturing enterprise.(2) According to the characteristics of the building materials equipment manufacturing enterprises and quality management methods, the paper analyzed the process quality control and established the process control model that based on the technology of data mining.(3) Analyzed the BP neural network and rough set theory and designed based on BP neural network and rough set collection of hybrid algorithm. Then, presented the concrete implementation steps and the process of the algorithm. Finally, given the calculation and simulating example to verify the feasibility of the method by combining the building materials equipment manufacturing enterprise of the actual manufacturing process.(4) In a building materials equipment manufacturing enterprise as the object, and designed and developed the quality of the building materials equipment manufacturing enterprise management subsystem based on investigating and analyzing business process of the enterprise. And the system has obtained the good application in the enterprise which is as an important part of enterprise digital manufacture platform. Meanwhile, it has Applied for the certificate of computer software copyright.(5) At last, the paper summarizes and prospects the work of the whole work.The research results of this paper are helpful to improve the quality of product process control for building materials, and also promote the building materials products to serve the equipment manufacturing industry better, and have the important engineering application value.
Keywords/Search Tags:Building materials equipment enterprise, Process quality control, Data Mining, BP Neural Network, Rough Set
PDF Full Text Request
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