Printed Circuit Board Surface Mount Production Process Quality Control System

With electronic products's development orientation toward smaller, thinner, small quantity and variety, Surface Mounting Technology (SMT) manufacturing process becomes more complex, traditional quality management becomes more and more difficult to adapt to the increasingly stringent quality management requirements. The SMT production line data acquisition system stored a mass amount of data, which implied a lot of knowledge; data mining can intelligently and automatically extract the valuable knowledge and information hidden in the large database. This thesis focuses on the specialty of modern SMT production line and the traditional production quality management system, using data mining to research and develop an open, scalable, intelligent new SMT production quality control system.This thesis introduced the decision tree algorithm of data mining technology, and based on the analysis of SMT production line to set up the flow of the mining production line data. Then, the discretization algorithm is proposed to let the decision tree algorithm in general be capable of handling continuous-valued attributes, also the AdaBoost reinforcement learning machine algorithm is introduced to improve the accuracy of the algorithm. Finally, we achieved an improved decision tree algorithm, which can effectively analyse the historical data of SMT production line to get the criteria evaluation of process parameters to support technicians for an optimization of the process parameters.In this thesis the author did a research about the application of Apriori algorithm, introduced the idea of supervised learning to improve the Apriori algorithm, and applied to diagnose the product defects. Finally, the improved algorithm we achieved is more efficient than the original Apriori algorithm, and can assist the technicians to faster solve the quality defects problem.Finally, in this thesis the development of the product quality control system software is base on the combination of Visual Basic.NET 2005 environment, SQL Server 2005 database system and network communication technology. After the experiment of the system on the real product line, the results indicated that the evaluation of process parameters function has a high accuracy and the defect diagnosis function has the right practicability.