• Industrial Engineering and Management Systems
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• 제8권3호
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• pp.139-147
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• 2009

Control charts are used to distinguish between chance and assignable causes in the variability of quality characteristics. When a control chart signals that an assignable cause is present, process engineers must initiate a search for the assignable cause of the process disturbance. Identifying the time of a process change could lead to simplifying the search for the assignable cause and less process down time, as well as help to reduce the probability of incorrectly identifying the assignable cause. The change point estimation by likelihood theory and the built-in change point estimation in a control chart have been discussed until now. In this article, we discuss two kinds of process change point estimation when the CUSUM ($\bar{x}$, s) control chart for monitoring process mean and variance simultaneously is operated. Throughout some numerical experiments about the performance of the change point estimation, the change point estimation techniques in the CUSUM ($\bar{x}$, s) control chart are considered.

• 대한산업공학회지
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• 제41권6호
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• pp.521-529
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• 2015

Statistical process control techniques have been greatly implemented in industries for improving product quality and saving production costs. As a primary tool among these techniques, control charts are widely used to detect the occurrence of assignable causes. In most works on the control charts it considered the problem of monitoring the mean and variance, and the quality characteristic of interest is normally distributed. In some situations monitoring of the minimum and maximum values is more important and the quality characteristic of interest is the Weibull distribution rather than a normal distribution. In this paper, we consider the statistical design of minimum and maximum control charts when the distribution of the quality characteristic of interest is Weibull. The proposed minimum and maximum control charts are applied to the wind data. The results of the application show that the proposed method is more effective than traditional methods.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.261-269
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• 2015

Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

• Journal of the Korean Data and Information Science Society
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• 제26권4호
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• pp.1027-1034
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• 2015

A control chart is very useful in monitoring various production process. There are many situations in which the simultaneous control of two or more related quality variables is necessary. When the joint distribution of the process variables is multivariate normal, multivariate Shewhart control charts using the function of the maximum likelihood estimator for monitoring the dispersion matrix are considered for the simultaneous monitoring of the dispersion matrix. The performances of the multivariate Shewhart control charts based on the proposed control statistic are evaluated in term of average run length (ARL). The performance is investigated in three cases, where the variances, covariances, and variances and covariances are changed respectively. The numerical results show that the performances of the proposed multivariate Shewhart control charts are not better than the control charts using the trace of the covariance matrix in the Jeong and Cho (2012) in terms of the ARLs.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.825-833
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• 2003

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 a maximum likelihood estimator of the process change point when a Shewhart $\bar{X}$ chart with variable sample size (VSS) scheme signals a change in the process mean. Also we build a confidence interval for the process change point by using the likelihood function.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2004년도 품질경영모델을 통한 가치 창출
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• pp.436-441
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• 2004

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 a generalized maximum likelihood estimate. (MLE) of the process change point when a control chart with variable sample size (VSS) scheme signals a change in the process mean, and evaluate the performance of this estimator when it mi used with a VSS EWMA chart.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.155-167
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• 2007

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 mean of a process in which the observations can be modeled as an AR(1) process plus an additional random error. The performance of the proposed MLE is compared to the performance of the built-in estimator when they are used in EWMA charts based on the residuals. The results show that the proposed MLE provides good performance in terms of both accuracy and precision of the estimator.

• Journal of the Korean Data and Information Science Society
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• 제20권2호
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• pp.435-443
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• 2009

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.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.963-972
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• 2007

When a control chart signals that a special cause is present, process engineers must initiate a search for and an identification of the special cause. Knowing the time of the process change could lead to identify the special cause more quickly, and to take the appropriate actions immediately to improve quality. 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 first-order autoregressive(AR(1)) process plus an additional random error.

• 응용통계연구
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• 제28권5호
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• pp.907-920
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• 2015

기하분포에 기초한 관리도는 불량품이 드물게 발생하는 고품질공정에서 불량률의 변화를 효율적으로 탐지할 수 있다고 알려져 있다. 이러한 관리도를 사용할 때 기본적인 가정은 관리상태일 때의 불량률이 알려져 있거나 또는 정확하게 추정되었다는 것이다. 그러나 고품질공정에서 불량률은 아주 작기 때문에 이를 정확하게 추정하기가 쉽지 않으며 또한 아주 큰 표본크기가 필요한 경우도 종종 발생한다. 일반적으로 제1국면에서 관리상태의 불량률을 추정할 때 최대우도추정량을 사용하지만, 이 논문에서는 베이즈추정량의 사용을 제안하였다. 베이즈추정량을 사용할 경우 실무자의 사전지식을 반영할 수 있으며 표본에 불량품이 발견되지 않을 경우 발생하는 최대우도추정량의 문제점을 해결할 수 있다는 장점이 있다. 기하 관리도와 기하누적합 관리도에서 베이즈추정량을 사용한 경우와 최대우도추정량을 사용한 경우를 비교한 결과, 표본의 크기가 크지 않은 경우 베이즈추정량을 사용하는 것의 효율이 더 좋음을 알 수 있었다.