Application of the Neural Network in developing an on-line real-time monitoring and diagnostic system for DES process of PCB

• Main Authors: Long-Lin Lee, 李龍麟
• Other Authors: Pei-Chann Chang
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/48296137806989740182

碩士 === 元智大學 === 工業工程研究所 === 89 === In this research, we developed an on-line real-time monitoring and diagnostic system for the Develop, Etch and dry film Strip (i.e., DES process) operations in the Printed Circuit Board (PCB) factory. From the empirical data of PCB factory, quality is affected by several key factors. Consequently, key factors that influenced the process should be identified first and through statistical regression analysis. The neural network expert control system is used to implement the real-time diagnostics and decisions will be made according to the input on-line captured from the system. Moreover, the criterion, root mean square error is used to evaluate the performances of case-base reasoning and backpropagation neural network. The comparisons result in that backpropagation neural network approach is superior to the case-base reasoning in this research.