Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Change point estimators in monitoring the parameters of an IMA(1,1) model

누적이동평균(1,1) 모형에서 공정 변화시점의 추정

  • Lee, Ho-Yun (Department of Statistics, Chung-Ang University) ;
  • Lee, Jae-Heon (Department of Statistics, Chung-Ang University)
  • 이호윤 (중앙대학교 대학원 통계학과) ;
  • 이재헌 (중앙대학교 수학통계학부)
  • Published : 2009.03.31
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Abstract

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose the maximum likelihood estimator (MLE) for the process change point when a control chart is used in monitoring the parameters of a process in which the observations can be modeled as a IMA(1,1).

생산 공정에서 관리도를 통하여 이상원인을 탐지하는 경우 이상상태의 신호가 발생하면 교정활동을 통하여 이를 규명하고 제거한 후 다시 공정을 가동시키는 것이 일반적이다. 이때 이상원인이 발생한 시점인 공정의 변화시점을 알 수 있다면 보다 빠르고 정확하게 이상원인을 규명하고 이를 제거할 수 있을 것이다. 이 논문에서는 누적이동평균(1,1) 모형, 즉 IMA(1,1) 모형을 따르는 공정에서 관리도를 사용하여 모수들의 변화를 탐지하는 경우 공정의 변화시점에 대한 MLE를 제안하고, 제안된 추정량의 효율에 대하여 연구하였다.

Keywords

References

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