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CQM-Oriented QFD Method Research

Posted on:2008-08-12Degree:MasterType:Thesis
Country:ChinaCandidate:X B MaFull Text:PDF
GTID:2189360272968405Subject:Industrial Engineering
Abstract/Summary:PDF Full Text Request
With the development of product requirements of diversification and customization , and the enlargement of requirements range of product quality, Collaborative Quality Management (CQM), as a new model of the Quality Management, has been paid attention by the enterprises and institutions in the world. One of the keys to actualize the Collaborative Quality Management is to analysize and to model the quality information flows. A Quality Function Deployment (QFD) method oriented to Collaborative Quality Management is proposed in this paper.Firstly, current researches on Collaborative Quality Management and QFD are introduced separately. On this basis, the conception and characteristics about quality information flows are discussed, and the collaborative models of quality information flows are built.Technologies of customer requirements analysis and information treatment are discussed. The analysis model of QFD requirements based on rough set is presented. The total process about modeling is discussed, the rough set algorithm based on discernible matrix is realized, which is validated by evaluation.Based on knowledge analysis, the estimation model of four-order QFD is built. The general method of fourth order QFD is discussed, and the four-order quality characteristics of automobile is built. Using two characteristics weights of before and after rough process, four-order deployment is implemented. Comparing to the change between two characteristics weights, optimization function of rough set is validated further.Finally, software environment and composition of Collaborative Quality Management System are introduced. The quality requirements management part and rough set algorithm are implemented. Then, the effect on characteristics weights from rough set is validated.
Keywords/Search Tags:Quality Function Deployment, Collaborative Quality Management, Rough Set, Quality Information Flow, Data Mining
PDF Full Text Request
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