• 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.

• 품질경영학회지
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• 제34권4호
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• pp.102-109
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• 2006

This paper investigates the effects of non-normality on the performance of univariate and multivariate cumulative sum(CUSUM) control charts for monitoring the process mean. In-control and out-of-control average run lengths of the charts are examined for the univariate/multivariate lognormal and t distributions. The effects of the reference value and the correlation coefficient under the non-normal distributions are also studied. Simulation results show that the CUSUM charts with small reference values are robust to non-normality but those with moderate or large reference values are sensitive to non-normal data especially to process data from skewed distributions. The performance of the chart to detect mean shift of a process is not invariant to the direction of the shift for skewed distributions.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.1003-1010
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• 2004

Properties of the variable sampling interval(VSI) CUSUM chart for monitoring dispersion matrix of related quality characteristics are investigated. Performances of the proposed charts are evaluated for matched fixed sampling interval(FSI) and VSI charts in terms of average time to signal(ATS) and average number of samples to signal (ANSS). Average number of swiches(ANSW) of the proposed VSI Shewhart and CUSUM charts are also investigated.

• Communications for Statistical Applications and Methods
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• 제4권3호
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• pp.715-723
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• 1997

Multivariate control statistics to simultaneously monitor both means and variances for several quality variables under multivariate normal process are proposed. Performances of the proposed multivariate charts are evaluated in terms of average run length(ARL). Multivariate Shewhart chart is also proposed to compare the performances of multivariate exponentially weighted moving average(EWMA) charts. A numerical comparison shows that multivariate EWMA charts are more efficient than multivariate Shewhart chart for small and moderate shifts and multivariate EWMA scheme based on accumulate-combine approach is more efficient than corresponding multivariate EWMA chart based on combine-accumulate approach.

• 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.

• International Journal of Quality Innovation
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• 제2권1호
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• pp.30-49
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• 2001

This paper considers a recent environment in the manufacturing process in which data in large amounts can be obtained on-line in real-time. Under this environment an on-line real-time Statistical Process Control (SPC) scheme equipped with detection of a process change, change-point estimation, and recognition of the change pattern is proposed. The proposed SPC scheme is composed of a Cusum chart, filtering methods and Akaike Information Criterion (AIC). We examine the performance of this scheme by Monte Carlo simulation and show its usefulness.

• International Journal of Quality Innovation
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• 제1권1호
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• pp.81-88
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• 2000

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.860-869
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• 2011

It is very important that reduce the maintenance cost and extend life time of the urban transit EMU through effective maintenance method research. The maintenance cost of the urban transit EMU shares 60%~70% of it's life cycle cost. It means that the maintenance cost is bigger than the introduction cost of the urban transit EMU. In this study, I introduces a quality control technique to improve the urban transit vehicle reliability. I suggest the control chart using quality control technique. And the control charts apply to the Static Inverter of EMU.

• 한국경영과학회지
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• 제12권1호
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• pp.111-111
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• 1987

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• Journal of the Korean Data and Information Science Society
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• 제26권6호
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• pp.1353-1366
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• 2015

공정의 안정성을 평가하기 위해 사용되는 Shewhart 관리도 기법은 최근 다양한 분야에서 널리 응용되고 있지만, 품질 특성치에 대한 엄격한 확률분포를 가정한다. 하지만 현업에서 수집되고 있는 데이터의 확률분포는 알려진 경우가 많지 않으며, 다변량 데이터로 확장될수록 확률분포를 결정하는데 더 큰 어려움이 따른다. 이러한 문제점을 해결하기 위해 다양한 비모수 관리도 기법이 연구되었는데, 최근 연구되고 있는 비모수 관리도 기법 중 하나인 RBF (Radial Basis Function) 커널 기반의 SVDD (Support Vector Data Description) 관리도는 관리상태 하의 데이터 영역에 대한 경계를 결정함으로써 공정의 이상상태를 탐지하는 기법으로 K 관리도로 불리우며, 다양한 분야에서 적용되고 있다. 그런데 K 관리도를 적용하기 위해서는 관리도의 성능을 결정짓는 커널모수 등의 선택이 중요하며, 관리도를 작성하기 전에 미리 결정되어야 한다. 이를 위해 기존의 연구들은 격자 탐색법 등을 활용하여 모수를 결정하고 있지만, 선택 가능한 범위에 대한 반복적인 계산으로 최적값을 선택하고 있어 계산 비용이 커지고 또 시간 등의 문제로 실제 문제에 적용하기 어려운 점이 있다. 따라서 본 연구에서는 데이터의 구조에 따라 모의실험을 통해 선택 가능한 영역에서의 효율성을 비교 검토하고, 이를 바탕으로 쉽게 적용할 수 있는 새로운 모수 선택 방법을 제안하고자 한다. 이를 통해 데이터 구조에 대해 강건함을 보이는 모수의 선택과 K 관리도의 구성을 논의하고 실제 자료에 적용해 보았다.