Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Software Engineering > Software Development

The software design and implementation of the the clothing quality prediction system

Author ZhaoZuo
Tutor YuanYuan;TianLiChao
School University of Electronic Science and Technology
Course Software Engineering
Keywords Rough Set Clothing Quality Prediction Knowledge Base Expert System
CLC TP311.52
Type Master's thesis
Year 2011
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With the increase of clothing styles and people’s requirements of clothing quality, clothing enterprises were forced to improve the prevention and controlling of clothing quality. Traditional manual administration mode lacks efficiency and is unable to guarantee the quality of its products. As an important constituent of clothing enterprise information management system, production tracking system stores large amount of data related to clothing quality. Therefore, it is necessary to make full use of these data to develop a convenient, quick and accurate clothing quality testing method which can make the apparel company deciders predict the clothing quality problem in advance and improve the companies’product quality and production efficiency.Clothing quality problem prediction is used to process inaccurate information. As a method to analyze inaccurate or uncertain information, rough sets theory is widely applied in various areas. Combining with the data mining technology, this article uses rough sets theory to develop the clothing quality prediction system. The main works which have been done in this article are as follows:The clothing quality prediction model has been built to generate quality problem rules and, meanwhile, to get the rules about the relationship between quality problem and machining process. Combining the characteristics of clothing production and referring tracking system according to the table in production quality problem, this model establishes the decision table consulted the data mining process which is based on rough set theory by using condition combination fill method to realize the completion process. Moreover, Naive Scaler algorithm is adopted to carry out sample data discretization, and Johnson’s algorithm is used to execute condition attributes reduction.Design the knowledge base via the research to generate rules. Considering the clothing production characteristics, the quality problem forecast has been done by the way of forward inference. The practical application and the rules filtration can guarantee the practicality of knowledge base.The clothing quality prediction system has been designed and implemented. A series of operations, including data collection, quality prediction and problem solving, has been realized. The expert knowledge base has been built via the clothing enterprise quality experts’guidance. The expert system which is achieved through access the information in knowledge base is used to analyze the prediction result and meanwhile, proposes solutions.

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