tailieunhanh - Neural Network Applications to Manufacturing Processes: Monitoring and Control

The nature of today’s manufacturing systems is changing with greater speed than ever and is becoming tremendously sophisticated due to rapid changes in their environments that result from customer demand and reduced product life cycle. | Suck Cho Hyung Neural Network Applications to Manufacturing Processes Monitoring and Control Computational Intelligence in Manufacturing Handbook Edited by Jun Wang et al Boca Raton CRC Press LLC 2001 12 Neural Network Applications to Manufacturing Processes Monitoring and Control Hyung Suck Cho Korea Advanced Institute of Science and Technology KAIST Introduction Manufacturing Process Monitoring and Control Neural Network-Based Monitoring Quality Monitoring Applications Neural Network-Based Control Process Control Applications Conclusions Introduction The nature of today s manufacturing systems is changing with greater speed than ever and is becoming tremendously sophisticated due to rapid changes in their environments that result from customer demand and reduced product life cycle. Accordingly the systems have to be capable of responding to the rapid changes and solving the complex problems that occur in various manufacturing steps. The monitoring and control of manufacturing processes is one of the important manufacturing step that requires the capabilities described in the above. Monitoring of the process state is comprised of three major steps carried out on-line i the process is continuously monitored with a sensor or multiple sensor ii the sensor signals are conditioned and preprocessed so that certain features and peaks sensitive to the process states can be obtained iii by pattern recognition based on these the process states are identified. Control of the process state is usually meant for feedback control and is comprised of the following steps i identifying the dynamic characteristics of the process ii measuring the process state iii correcting the process operation observing the resulting product quality and comparing the observed with the desired quality. It is noted that in the last step the observed state needs to be related to product quality. Normal operation of the above-mentioned steps should not be .