| Summary: | 碩士 === 元智大學 === 資訊管理學系 === 90 === The application of Neuro-Fuzzy on the optimization
process of the PCB Laminate
Student：Yih-Min Yang Advisor：Dr. Hsi-Chieh Lee
Department of Information Management
Yuan-Ze University
ABSTRACT
The application of the traditional PID controller is currently the most popular approach for temperature control in the PCB laminate manufacturing process in the electronics industry. Traditional PID controller works quite well when constant temperature control is required. However, it is never a trivial job to apply the traditional PID controller effectively for control specific ascending descending curve. Consequently, it is even more difficult applying PID controller for optimize control.
In this study, neuro-fuzzy approach is utilized in an attempt to optimize the PCB laminate manufacturing process. A PC-based fuzzy controller is designed to realize the function of the temperature ascending/descending curve for the PCB laminate manufacturing process. Neural network is used in the fuzzy controller in order to learn the membership function from the trained data. Meanwhile, this neuro-fuzzy controller can also be integrated with PLC system, the de facto standard that is widely adopted for achieving the optimization control.
Experimental results from simulated PCB laminate process control have shown the feasibility and usefulness of the neuro-fuzzy controller. Due to the nature the process control, it is not too difficult to modify the neuro-fuzzy controller for the optimization of PCB laminate process for other similar process optimization control.
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