• 대한산업공학회지
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• 제42권6호
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• pp.395-403
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• 2016

In mobile industry, using a metal frame of devices is rapidly increased for thin and stylish designs. However, fabricating metal is one of the difficult processes because the sophisticated control of equipment is required during the whole machining time. In this study, we present an efficient multivariate monitoring procedure for the metal frame process in mobile device manufacturing. The effectiveness of the proposed procedure is demonstrated by real data from the mobile plant in one of the leading mobile companies in South Korea.

• 대한수학회논문집
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• 제17권1호
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• pp.95-102
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• 2002

A central limit theorem is obtained for a stationary multivariate linear process of the form (equation omitted), where { $Z_{t}$} is a sequence of strictly stationary m-dimensional associated random vectors with E $Z_{t}$ = O and E∥ $Z_{t}$∥$^2$ < $\infty$ and { $A_{u}$} is a sequence of coefficient matrices with (equation omitted) and (equation omitted).ted)..ted).).

• Communications for Statistical Applications and Methods
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• 제12권1호
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• pp.71-86
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• 2005

Testing for normality has always been an important part of statistical methodology. In this paper a test statistic for multivariate normality is proposed. The underlying idea is to investigate all the possible linear combinations that reduce to the standard normal distribution under the null hypothesis and compare the order statistics of them with the theoretical normal quantiles. The suggested statistic is invariant with respect to nonsingular matrix multiplication and vector addition. We show that the limit distribution of an approximation to the suggested statistic is representable as the supremum over an index set of the integral of a suitable Gaussian process.

• 품질경영학회지
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• 제40권3호
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• pp.337-346
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• 2012

Purpose: A Control chart is one of the important statistical process control tools that can improve processes by reducing variability and defects. Methods: In the present study, we propose the local $T^2$ multivariate control chart that can efficiently detect abnormal observations by considering the local pattern of the in-control observations. Results: A simulation study has been conducted to examine the property of the proposed control chart and compare it with existing multivariate control charts. Conclusion: The results demonstrate the usefulness and effectiveness of the proposed control chart.

• 응용통계연구
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• 제25권4호
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• pp.589-603
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• 2012

Mahalanobis-Taguchi system(MTS) is a statistical tool for classifying the normal group and abnormal group in multivariate data structures. In addition to the classification itself, the MTS uses a method for selecting variables useful for the classification. This method can be used efficiently especially when the abnormal group data are scattered without a specific directionality. When the feedback adjustment procedure through the measurements of the process output for controlling process input variables is not practically possible, the reset procedure can be an alternative one. This article proposes a reset procedure using the MTS. Moreover, a method for identifying input variables to reset is also proposed by the use of the contribution. The identification of the root-cause parameters using the existing dimension-reduced contribution tends to be difficult due to the variety of correlation relationships of multivariate data structures. However, it became possible to provide an improved decision when used together with the location-centered contribution and the individual-parameter contribution.

• 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.

• 응용통계연구
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• 제26권2호
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• pp.281-290
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• 2013

DD-plot은 분류문제를 풀기 위한 유용한 비모수적 방법이다. 우리는 이러한 DD-plot을 다변량공정에서 이상상태를 탐지하기 위한 그래픽 방법으로 사용할 수 있다. 본 논문을 통하여 이상상태를 탐지하기 위한 그래픽 방법으로서 동적 DD-plot과 동적 품질지수그림을 제시하고자 한다.

• 한국정보통신학회논문지
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• 제24권2호
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• pp.192-197
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• 2020

대규모 발전소나 화학공정과 같은 다변량 공정은 매우 위험한 환경에서 운전되기 때문에 고장이 발생하면 심각한 인적·물적 손실이 발생할 수 있다. 따라서 시스템의 고장을 사전에 탐지할 수 있는 온라인 모니터링 기술이 필수적이다. 본 논문에서는 세 가지의 다른 다변량 공정 데이터에 ICA를 적용하여 고장탐지를 수행하였고, PCA와 성능을 비교하였다. ICA 기반의 고장탐지 절차는 크게 오프라인 과정과 온라인 과정으로 나뉜다. 오프라인 과정에서는 시스템이 정상일 때 계측된 데이터를 이용하여 고장판별을 위한 문턱 값을 설정한다. 그리고 온라인 과정에서는 실시간으로 계측되는 질의벡터에 대한 통계량을 계산한 후, 계산된 통계량과 사전에 정의된 문턱 값과 비교하여 고장을 판별한다. 본 논문에서 이용한 세 가지의 다변량 공정 데이터에 실험한 결과, ICA 기반 고장탐지 방법이 시스템의 고장을 사전에 탐지하였고, PCA 보다 우수한 고장탐지 성능을 보여주었다.

• 품질경영학회지
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• 제25권3호
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• pp.39-50
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• 1997

Markov chain method to evaluate the properties of control charts with variable sampling intervals(VSI0 for simultaneously monitoring several correlated quality characteristics under multivariate normal process are investigated. For comparing the efficiencies and properties of multivariate control charts, we consider multivariate Shewhart, CUSUM and EWMA charts in terms of average time to signal(ATS) and average number of samples to signal(ANSS). We obtained stabilized numerical results with Markov chain method when the number of transient state is greater than 100.

• 진공이야기
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• 제2권4호
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• pp.27-32
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• 2015

Plasma diagnosis and multivariate analysis techniques for plasma processes are reviewed. The principles and applications of optical emission spectroscopy (OES) and VI probe are discussed briefly. The research results of principal component analysis (PCA), one of the widely used multivariate analysis techniques for plasma process monitoring is discussed in this article.