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The Monitoring of PLC-Program using Neural Network
BM Mulman,In-Sung Jung,Jae-ho Bae,S.C.Park,Gi-Nam Wang 한국경영과학회 2008 한국경영과학회 학술대회논문집 Vol.2008 No.5
This paper reviews monitoring and validation of PLC-program using Neural Network. In the PLC-device controlled manufacturing line, PLC-program holds place of underlying component. It becomes controlling mechanism. The level of automation in the production line relies on control mechanism practiced. In the modern manufacturing, PLC devices can handle whole production line given that structured and smart PLC-program is executed. In other words, PLC-program can manage whole process structure consisting set of procedures. We present a method to monitor PLC-program and validate it using neural network. The neural network method being predictive in nature, it rigorously can monitor process signals from sensors, sensed during operation of PLC devices or execution of PLC-program. Subsequently, a neural network algorithm practiced for the analysis of signals. In this way, thorough monitoring of PLC-program can find possible errors from temporal parameters. In addition, possible alterations in program and irregularities can be minimized. That can result, ease in fault detection, maintenance, and decision support in manufacturing organization. Similarly, it can lessen down-time of machines and prevent possible risks.
The Monitoring of PLC-Program using Neural Network
BM Mulman,In-Sung Jung,Jae-ho Bae,S.C.Park,Gi-Nam Wang 대한산업공학회 2008 대한산업공학회 춘계학술대회논문집 Vol.2008 No.5
This paper reviews monitoring and validation of PLC-program using Neural Network. In the PLC-device controlled manufacturing line, PLC-program holds place of underlying component. It becomes controlling mechanism. The level of automation in the production line relies on control mechanism practiced. In the modern manufacturing, PLC devices can handle whole production line given that structured and smart PLC-program is executed. In other words, PLC-program can manage whole process structure consisting set of procedures. We present a method to monitor PLC-program and validate it using neural network. The neural network method being predictive in nature, it rigorously can monitor process signals from sensors, sensed during operation of PLC devices or execution of PLC-program. Subsequently, a neural network algorithm practiced for the analysis of signals. In this way, thorough monitoring of PLC-program can find possible errors from temporal parameters. In addition, possible alterations in program and irregularities can be minimized. That can result, ease in fault detection, maintenance, and decision support in manufacturing organization. Similarly, it can lessen down-time of machines and prevent possible risks.