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A Comparative Analysis on the Efficiency of Monitoring between EWMA and Shewhart Chart in Instrumental Process with Autocorrelation

자기상관이 있는 장치 공정에서 EWMA와 Shewhart 관리도와의 모니터링 효율성 비교 분석

  • Cho, Jin-Hyung (Division of Industrial Engineering, Kumoh National Institute of Technology) ;
  • Oh, Hyun-Seung (Department of Industrial Engineering and Management, Hannam University) ;
  • Lee, Sae-Jae (Division of Industrial Engineering, Kumoh National Institute of Technology) ;
  • Jung, Su-Il (Division of Industrial Engineering, Kumoh National Institute of Technology) ;
  • Lim, Taek (Division of Industrial Engineering, Kumoh National Institute of Technology) ;
  • Baek, Seong-Seon (Division of Industrial Engineering, Kumoh National Institute of Technology) ;
  • Kim, Byung-Keug (Division of Industrial Engineering, Kumoh National Institute of Technology)
  • 조진형 (금오공과대학교 산업공학부) ;
  • 오현승 (한남대학교 산업경영공학과) ;
  • 이세재 (금오공과대학교 산업공학부) ;
  • 정수일 (금오공과대학교 산업공학부) ;
  • 임택 (금오공과대학교 산업공학부) ;
  • 배성선 (금오공과대학교 산업공학부) ;
  • 김병극 (금오공과대학교 산업공학부)
  • Received : 2012.08.30
  • Accepted : 2012.10.28
  • Published : 2012.12.31

Abstract

When monitoring an instrumental process, one often collects a host of data such as characteristic signals sent by a sensor in short time intervals. Characteristic data of short time intervals tend to be autocorrelated. In the instrumental processes often the practice of adjusting the setting value simply based on the previous one, so-called 'adjacent point operation', becomes more critical, since in the short run the deviations are harder to detect and in the long run they have amplified consequences. Stochastic modelling using ARIMA or AR models are not readily usable here. Due to the difficulty of dealing with autocorrelated data conventional practice is resorting to choosing the time interval where autocorrelation is weak enough then to using I-MR control chart to judge the process stability. In the autocorrelated instrumental processes it appears that using the Shewhart chart and the time interval data where autocorrelation is relatively not existent turns out to be a rather convenient and very useful practice to determine the process stability. However in the autocorrelated instrumental processes we intend to show that one would presumably do better using the EWMA control chart rather than just using the Shewhart chart along with some arbitrarily intervalled data, since the former is more sensitive to shifts given appropriate weights.

Keywords

Acknowledgement

Supported by : Kumoh Nat'l Institute of Technology

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