• 응용통계연구
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• 제25권3호
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• pp.465-470
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• 2012

EWMA(exponentially weighted moving average) charts and CUSUM(cumulative sum) charts are very effective to detect small shifts in the process mean. These charts have some control-chart parameters that allow the charts and be tuned and be more sensitive to certain shifts. The EWMA chart requires users to specify the value of a smoothing parameter, which can also be designed for the size of the mean shift. However, the size of the mean shift that occurs in applications is usually unknown and EWMA charts can perform poorly when the actual size of the mean shift is significantly different from the assumed size. In this paper, we propose the design procedure to find the optimal smoothing parameter of the EWMA chart when the size of the mean shift is unknown.

• 품질경영학회지
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• 제26권1호
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• pp.108-125
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• 1998

The EWMA(Exponentially Weighted Moving Average) has recently received a great deal of attention in the quality control literature as a process monitoring tool on the shop floor of manufacturing industires, since it is easy to plot, to interpret, and its control limits are easy to obtain. Most a, pp.ications of the EWMA for process monitoring have concentrated on the problem of detecting shifts of a process mean and a process standard deviation with ARL(Average Run Length) properties. But there may be the necessity of controlling linearity on product quality such as the correlation coefficient to the process operator. Control managers may want to protect the increase of a process correlation coefficient value, such as 0, between two variables of interest. However, there are few studies concerned on this part. Therefore, we propose EWMA models for a process correlation coefficient using two transformed statistics, T-statistic and (Fisher's) Z-statistic. We also present some results of simulation by SAS/IML and compare two models.

• 한국시뮬레이션학회논문지
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• 제16권4호
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• pp.43-55
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• 2007

생산 공정 제어방법들 중에서 이동평균 제어와 지수가중치 이동평균 제어는 가장 널리 사용되는 제어이다. 두 제어는 모두 정확한 제어식을 알고 있다는 전제 하에 최적화된 제어들이다. 이 논문에서는 제어식의 잘못된 예측으로부터 발생하는 문제점에 대해 다루었다. 추정한 모수의 정확도와 가중치 $\lambda$의 범위에 의해 결정되는 각각의 제어방식의 제어한계에 대해서 확인하고 제어 간의 성능을 평가하였다. 또한 잘못 추정된 모델이 존재하는 공정에서 Shift가 발생하였을 때 최적의 제어와 그것을 실제 공정에서 어떻게 적용할지에 대해서 연구하였다. 시뮬레이션을 통해 제안하는 방법의 효용성을 검증하였다.

• 대한안전경영과학회지
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• 제12권4호
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• pp.255-263
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• 2010

The research developes short-run standardized control charts(SSCC) and short-run acceptance control charts(SACC) under the various demand patterns. The demand patterns considered in this paper are three types such as high-variety and repetitive low-volume pattern, extremely-high-variety and nonrepetitive low-volume pattern, and high-variety and extremely-low-volume pattern. The short-run standardized control charts developed by extending the long-run ${\bar{x}}$-R, ${\bar{x}}$-s and I-MR charts have strengths for practioners to understand and use easily. Moreover, the short-range acceptance control charts developed in the study can be efficiently used through combining the functions of the inspection and control chart. The weighting schemes such as Shewhart, moving average (MA) and exponentially weighted moving average (EWMA) can be considered by the reliability of data sets. The two types according to the use of control chart are presented in the short-range standardized charts and acceptance control charts. Finally, process capability index(PCI) and process performance index(PPI) classified by the demand patterns are presented.

• 대한안전경영과학회지
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• 제12권3호
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• pp.257-262
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• 2010

The study investigates the various Acceptance Control Charts (ACCs) based on the factors that include process independence, data weighting scheme, subgrouping, and use of control charts. USL - LSL > $6{\sigma}$ that used in the good condition processes in the ACCs are designed by considering user's perspective, producer's perspective and both perspectives. ACCs developed from the research is efficiently applied by using the simple control limit unified with APL (Acceptable Process Level), RLP (Rejectable Process Level), Type I Error $\alpha$, and Type II Error $\beta$. Sampling interval of subgroup examines i.i.d. (Identically and Independent Distributed) or auto-correlated processes. Three types of weight schemes according to the reliability of data include Shewhart, Moving Average(MA) and Exponentially Weighted Moving Average (EWMA) which are considered when designing ACCs. Two types of control charts by the purpose of improvement are also presented. Overall, $\alpha$, $\beta$ and APL for nonconforming proportion and RPL of claim proportion can be designed by practioners who emphasize productivity and claim defense cost.

• 전자공학회논문지
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• 제50권1호
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• pp.196-204
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• 2013

본 논문에서는 WDRR(Weighted Deficit Round Robin) 기법을 토대로 군사 위성통신망의 QoS를 향상시키기 위한 스케줄링 기법을 제안한다. 제안된 동적 WDRR기법은 통신망 대기열의 패킷의 크기가 커지는 경우 지수이동평균을 이용, 적절한 추가 퀀텀을 부여하여 대기열의 패킷을 효율적으로 전송하는 방법이다. 제안된 알고리즘의 효용성을 증명하기 위해 OPNET Modeler를 이용하여 모의실험환경을 구축하고, 제안된 알고리즘의 신뢰성 및 실시간성을 분석하였다. 이를 통하여, 기존 군사용 위성통신망 스케줄링 기법에 사용되는 WRR(Weighted Round Robin), DRR(Deficit Round Robin), WDRR(Weighted Deficit Round Robin) 등을 비교 분석한 모의실험 결과를 통해 통신망 지연시간과 패킷 손실율에 관한 성능 향상을 보였다.

• 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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• 제18권4호
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• pp.915-925
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• 2007

Multivariate GARCH has been useful to model dynamic relationships between volatilities arising from each component series of multivariate time series. Methodologies including EWMA(Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model) models are comparatively reviewed for bivariate time series. In addition, these models are applied to evaluate VaR(Value at Risk) and to construct joint prediction region. To illustrate, bivariate stock prices data consisting of Samsung Electronics and LG Electronics are analysed.

• 품질경영학회지
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• 제28권2호
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• pp.70-88
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• 2000

Short runs where it is neither possible nor practical to obtain sufficient subgroups to estimate accurately the control limit are common in modem business environments. In this study, the standardized control chart, Hillier's exact method, Q chart, EWMA(Exponentially Weighted Moving Average) chart for Q statistics and EWMA chart for mean and absolute deviation among many SPC(Statistical Process Control) techniques for short runs have been reviewed and advantages and disadvantages of these techniques are discussed. The simulation experiments to compare performances of these variable charts for process mean and variations are conducted for combination of subgroup size, scale and timing of shifts of process mean an/or standard deviation. Based upon simulation results, some guidelines for practitioners to choose short run SPC techniques are recommended.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.525-533
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• 2015

Modern production process is a very complex structure combined observations which are correlated with several factors. When the error signal occurs in the process, it is very difficult to know the root causes of an out-of-control signal because of insufficient information. However, if we know the time of the change, the system can be controlled more easily. To know it, we derive a maximum likelihood estimator (MLE) of the change point in a process when observations are from a multivariate IMA(1,1) process by monitoring residual vectors of the model. In this paper, numerical results show that the MLE of change point is effective in detecting changes in a process.