산업공학 (IE interfaces)

  • 제20권3호
  • /
  • Pages.288-297
  • /
  • 2007
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  • 1225-0996(pISSN)
  • /
  • 2234-6465(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
권호 표지

비동기 설비 신호 상황에서의 강건한 공정 이상 감지 시스템 연구

Robust Process Fault Detection System Under Asynchronous Time Series Data Situation

  • 고종명 (연세대학교 정보산업공학과) ;
  • 최자영 (연세대학교 정보산업공학과) ;
  • 김창욱 (연세대학교 정보산업공학과) ;
  • 선상준 (삼성전자 생산기술연구소) ;
  • 이승준 (삼성전자 생산기술연구소)
  • Ko, Jong-Myoung (Department of Information and Industrial Engineering, Yonsei University) ;
  • Choi, Ja-Young (Department of Information and Industrial Engineering, Yonsei University) ;
  • Kim, Chang-Ouk (Department of Information and Industrial Engineering, Yonsei University) ;
  • Sun, Sang-Joon (Manufacturing Innovation Team, Mechatronics and Manufacturing Technology Center, Samsung Electronics Co., Ltd.) ;
  • Lee, Seung-Jun (Manufacturing Innovation Team, Mechatronics and Manufacturing Technology Center, Samsung Electronics Co., Ltd.)
  • 투고 : 20070700
  • 심사 : 20070800
  • 발행 : 2007.09.30
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초록

Success of semiconductor/LCD industry depends on its yield and quality of product. For the purpose, FDC (Fault Detection and Classification) system is used to diagnose fault state in main manufacturing processes by monitoring time series data collected by equipment sensors which represent various conditions of the equipment. The data set is segmented at the start and end of each product lot processing by a trigger event module. However, in practice, segmented sensor data usually have the features of data asynchronization such as different start points, end points, and data lengths. Due to the asynchronization problem, false alarm (type I error) and missed alarm (type II error) occur frequently. In this paper, we propose a robust process fault detection system by integrating a process event detection method and a similarity measuring method based on dynamic time warping algorithm. An experiment shows that the proposed system is able to recognize abnormal condition correctly under the asynchronous data situation.

키워드

참고문헌

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