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김유석(Youseok Kim),김병환(Byungwhan Kim),권기청(Gichung Kwon),한정훈(Jeong Hoon Han),송종원(Jongwon Shon) 대한전기학회 2006 정보 및 제어 심포지엄 논문집 Vol.2006 No.1
Auto-Correlated time series (ATS) model was constructed by using the backpropagation neural network. The performance of ATS model was evaluated with sensor information collected from a large volume. industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 4%. By integrating ATS model into equipment software. process quality can be more stringently monitored while improving device throughput.