• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.11-14
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• 1996

Performance of the group cumulative sum(CUSUM) control scheme using multiple univariate CUSUM charts is more sensitive to the change of quality control(QC) characteristics than the control chart scheme based on the Hotelling statistics. We examine three group charts for multivariate normal data sets simulated with various correlation structures and shift directions in the mean vector. These group schemes apply the orginal measurement vectors, the scaled residual vectors from the regression of each variable on all others and the principal component vectors respectively to calculating the CUSUM statistics. They are also compared to the multivariate QC charts based on the Hotelling statistic by estimating average run lengths, coefficients of variation of run length and ranks in signaling order. On the basis of simulation results, we suggest a control chart scheme appropriate for specific quality control environment.

• Management Science and Financial Engineering
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• 제5권1호
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• pp.51-71
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• 1999

Performance of the group cumulative sum (CUSUM) control scheme using multiple univariate CUSUM charts is more sensitive to the change of quality control (QC) characteristics than the control chart schemes based on the Hotelling statistic We vexamine three group charts for multivariate normal data sets simulated with various correlation structures and shift directions in the mean vector. These group schemes apply the original measurement vectors, the scaled residual vectors from the re-gression of each variable on all others and the principal component vectors respectively to calculat-ing the CUSUM statistics. They are also compared to the multivariate QC charts based on the Ho-telling statistic by estimating average run lengths, coefficients of variation of run length and ranks in signaling order. On the basis of simulation results, we suggest a control chart scheme appropriate for specific quality control environment.

• Journal of the Korean Data and Information Science Society
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• 제23권3호
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• pp.617-626
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• 2012

Multivariate Shewhart control charts are considered for the simultaneous monitoring the variance-covariance matrix when the joint distribution of process variables is multivariate normal. The performances of the multivariate Shewhart control charts based on control statistic proposed by Hotelling (1947) are evaluated in term of average run length (ARL) for 2 or 4 correlated variables, 2 or 4 samples at each sampling point. The performance is investigated in three cases, that is, the variances, covariances, and variances and covariances are changed respectively.

• 대한안전경영과학회지
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• 제13권4호
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• pp.225-235
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• 2011

Autoregressed Controller, which have trend algorithm, seeks to minimize variability by transferring the output variable to the related process input variable, while multivariate process control techniques seek to reduce variability by detecting and eliminating assignable causes of variation. In the case of process control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We also investigate algorithm with relevant Shewhart chart, Theoretical control charts, precontrol and process capability. To help the people who want to make the theoretical system, we compare the main techniques in "a study on the relation between multivariate process control techniques and trend algorithms".

• 품질경영학회지
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• 제26권2호
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• pp.51-60
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• 1998

Exponetially weighted moving average(EWMA) control chart to simultaneously monitor correlation coefficients of several correlated quality variables under multivariate normal process are proposed. Performances of the proposed control charts are measured in terms of average run length(ARL) by simulation. Numerical results show that smaller values of smoothing constant are more efficient in terms of ARL.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.451-459
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• 2017

There are many researches showing that when a process change has occurred, variable sampling intervals (VSI) control chart is better than the fixed sampling interval (FSI) control chart in terms of reducing the required time to signal. When the process engineers use VSI control procedure, frequent switching between different sampling intervals can be a complicating factor. However, average number of samples to signal (ANSS), which is the amount of required samples to signal, and average time to signal (ATS) do not provide any control statistics about switching performances of VSI charts. In this study, we evaluate numerical switching performances of multivariate VSI EWMA chart including average number of switches to signal (ANSW) and average switching rate (ASWR). In addition, numerical study has been carried out to examine how to improve the performance of considered chart with accumulate-combine approach under several different smoothing constant and sample size. In conclusion, process engineers, who want to manage the correlation coefficients of related quality variables, are recommended to make sample size as large and smoothing constant as small as possible under permission of process conditions.

• 응용통계연구
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• 제31권1호
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• pp.1-11
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• 2018

최근 다변량 공정관리는 다양한 응용 분야에서 중요해지고 있는 추세이다. 예를 들어, 제조 산업 분야에서는 다변량 품질특성치를 동시에 모니터링할 필요가 있다. 그러나, 다변량 관리도는 이상신호가 발생한 경우 그 원인이 되는 개별적인 변수를 식별하기가 어렵기 때문에, 실제로는 기대만큼 유용하게 쓰이고 있지 않은 형편이다. 이에 본 논문에서는 새로운 관측치에 대한 개별적인 신뢰구간을 사용하여 이상신호의 원인을 탐지하는 세 가지 방법을 소개하고, 시뮬레이션 연구를 통해 이상신호의 원인이 되는 개별적인 변수를 식별하고 해석하는 데 있어 주의할 점이 무엇인지 살펴보기로 한다.

• Journal of the Korean Data and Information Science Society
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• 제21권6호
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• pp.999-1008
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• 2010

공정을 모니터링 하기 위한 전통적인 관리도는 표본들 사이의 일정한 추출간격에서 일정한 수의 표본을 취하여 만들어 지는 고정추출율 관리도이다. 본 연구의 목표는 표준적인 고정추출율을 갖는 다변량 관리도에 비하여 성능이 우수한 가변추출간격을 갖는 다변량 관리도를 개발하는데 있다. 대부분의 다변량 관리도에 대한 연구는 공정의 평균벡터를 모니터링 하는데 초점이 맞추어져 있다. 그러나 본 논문에서는 공정의 평균벡터와 분산-공분산을 동시에 모니터링 하기 위한 다변량 관리도를 연구한다. 가변추출간격을 갖는 다변량 슈하르트 관리도에 대하여 연구 하고자 한다.

• 한국컴퓨터정보학회논문지
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• 제12권4호
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• pp.201-207
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• 2007

제조업에서는 2개 이상의 상관이 있는 품질특성치를 동시에 감시하거나 관리를 하기 위한 필요성이 많이 제기되고 있다. 하지만 복수의 품질특성치를 각각 독립적으로 감시하면 판단의 오류가 발생될 수 있다. 복수의 품질특성치를 동시에 감시하고자 할 때 $X^2$ 또는 $T^2$와 같은 다변량 관리도가 사용되어질 수 있다. 본 논문에서는 다수의 품질특성치를 갖는 용해공정에서 조기에 이상 징후를 파악하기 위하여 다변량 관리도를 이용한 조기경보 시스템을 구현하였다. 용해공정에서 상관성이 있는 다수의 품질특성치를 동시에 관리하기 위해 개발된 이 모듈은 용해공정의 통계적 공정관리 활동에 효율성 및 효과성을 향상시켜 주었다.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.289-301
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• 2003

In this paper, we propose Shewhart control chart and EWMA control chart using the autocorrelated data which are common in chemical and process industries and lead to increase the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and simulation is conducted to investigate the performances of the proposed control charts.