The Design And Implementation Of Decision Tree-based Footwear Quality Assurance System

With economic development, footwear manufacturing enterprises have a greater volume of business growth, and thus have to undertake greater workload of product quality inspection. How to classify products quickly and accurately through using inspection data is the key to the product quality control. This thesis uses the data mining technology for the quality assessment issue in footwear segments.Firstly, we analyze the standard quality system for footwear products. In order to build the assessment model which meets the actual operation need of footwear manufacturing companies, we use the C4.5decision tree algorithm to construct a model for quality assessment of footwear and validate its effectiveness. Based on this model, we designed and implemented a quality assessment system for footwear manufacturing enterprise. The contributions are as follows:(1) We investigated the footwear product quality assessment requirements, and summarized the quality assessment standards footwear products; According to footwear GB standards, we used C4.5decision tree algorithm to construct quality evaluation model, and validated it.(2) After analyzing the requirements of a quality assessment system, we designed and implemented the system with the full understanding of its business processes, data flow, and data mining processes. And we also designed its conceptual database model and implemented it accordingly.(3) Based on ASP.NET and SQL Server2010, we finished the implementation of the quality management system.The system not only can quickly and accurately determine the quality of footwear products, but also help the business managers to grasp the trend of footwear product quality, make reasonable adjustments to the production line and avoid defective products. The system can also support targeted marketing and decision-making. It is of important practical value.