• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.221-231
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• 2006

A chi-squared test of multivariate normality is suggested which is oriented for detecting deviations from elliptical symmetry. We derive the limiting distribution of the test statistic via a central limit theorem on empirical processes. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under a non-normal distribution.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.265-273
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• 2005

In this paper, we proposed multivariate EWMA control charts for both combine-accumulate and accumulate-combine approaches to monitor dispersion matrix of multiple quality variables. Numerical performance of the proposed charts are evaluated in terms of average run length(ARL). The performances show that small smoothing constants with accumulate-combine approach is preferred for detecting small shifts of the production process.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.470-472
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• 2006

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as environment and health, industry scene system monitoring, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modem learning techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes having the capability of simple processing and wireless communication. The proposed system is able to perform context classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to intelligent dust collecting system.

• Journal of the Korean Data and Information Science Society
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• 제23권4호
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• pp.807-814
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• 2012

We know that the exponentially weighted moving average (EWMA) control charts are sensitive to detecting relatively small shifts. Multivariate EWMA control charts are considered for monitoring of variance-covariance matrix when the distribution of process variables is multivariate normal. The performances of the proposed EWMA control charts are evaluated in term of average run length (ARL). The performance is investigated in three types of shifts in the variance-covariance matrix, that is, the variances, covariances, and variances and covariances are changed respectively. Numerical results show that all multivariate EWMA control charts considered in this paper are effective in detecting several kinds of shifts in the variance-covariance matrix.

• 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.

• 품질경영학회지
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• 제49권4호
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• pp.539-550
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• 2021

Purpose: The purpose of this study is to propose a multivariate CUSUM control chart that can detect the out-of-control state fast while monitoring the cross- and auto- correlated multivariate time series data. Methods: We first build models to estimate the observation data and calculate the corresponding residuals. After then, a multivariate CUSUM chart is applied to monitor the residuals instead of the original raw observation data. Vector Autoregression and Artificial Neural Net are selected for the modelling, and Separated-MCUSUM chart is selected for the monitoring. The suggested methods are tested under a number of experimental settings and the performances are compared with those of other existing methods. Results: We find that Artificial Neural Net is more appropriate than Vector Autoregression for the modelling and show the combination of Separated-MCUSUM with Artificial Neural Net outperforms the other alternatives considered in this paper. Conclusion: The suggested chart has many advantages. It can monitor the complicated multivariate data with cross- and auto- correlation, and detects the out-of-control state fast. Unlike other CUSUM charts finding their control limits by trial and error simulation, the suggested chart saves lots of time and effort by approximating its control limit mathematically. We expect that the suggested chart performs not only effectively but also efficiently for monitoring the process with complicated correlations and frequently-changed parameters.

• 지능정보연구
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• 제9권1호
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• pp.53-69
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• 2003

현대의 생산공정에서는 많은 공정변수가 발생하고 있으며 복잡한 연관관계를 가지고 제품의 품질에 영향을 미치고 있다. 따라서 공정의 이상 유무 확인을 위해서는 많은 품질특성치를 동시에 관리하는 다변량 공정관리가 필요하다. 본 연구는 자기조직화 신경망(SOM)과 사례기반추론(CBR) 기법을 이용한 다변량 공정관리 방안을 제안한다. SOM을 이용하여 공정 데이터의 패턴을 생성하고 이상 유무 판단을 위해 기준패턴과 적합성 검정을 한다. 제안한 방법의 검증을 위해 공정에서 발생 가능한 패턴별로 데이터를 생성하여 실험하였고, 실험을 통해 이상패턴을 효과적으로 구별할 수 있음을 보였다. 또한 CBR 방법론을 적용하여 1종 오류는 줄이면서 2종 오류를 아주 작게 유지할 수 있음을 보임으로써, SOM과 CBR 이 결합된 절차가 다변량 공정관리를 위한 한 대안이 될 수 있음을 보였다.

• 대한안전경영과학회지
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• 제5권3호
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• pp.145-156
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• 2003

As we understand it, Process Capability indices are intended to provide single-number assessments of ability to meet specification limits on quality characteristics of interest. As a consequence of the varied ways in which PCIs are used, there have been two natural lines of research work: $\circled1$ studies on the properties of PCIs and their estimators in many different environments; $\circled2$ construction of new PCIs purporting to have better properties in certain circumstances. The most of existing process capability indices are concerned with the single variable. But, in many cases, a quality characteristic is composed with several factors. In that case, we want to know the integrated process capability of a quality characteristic not those of each factor. In this paper, we proposed a new multivariate system process capability index called $MSPCI:SC_{psk}$ which is the geometric mean of performance measure $C_{psk}$'S, and will be used as the criterion to assess multiple response process designs. Numerical illustration is done for $SC_{psk}$, $\overline{C_p}$(f), Cp, Cpk, Cpm, and Cpsk.

• Journal of the Korean Statistical Society
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• 제30권3호
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• pp.407-418
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• 2001

Buhlmann(1944) established the validity of the block bootstrap proposed by Kunsch when it is applied to p-dimensional $\alpha$-mixing dependent sequence. But his result requires a rather restrictive condition on p in the sense that p is entangled with dependence structure. We address that such restriction on p(or complication of dependence structure with p) could be removed completely when the underlying dependence structure is replace by more weakly dependent structure such as ø-mixing.

• 한국펄프종이공학회:학술대회논문집
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• 한국펄프종이공학회 2006년도 PAN PACIFIC CONFERENCE vol.2
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• pp.191-195
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• 2006

Multivariate data analysis tools were used to improve the understanding of the wet end chemistry and white water system of the Papermill at NorskeCanada Crofton Division. Specifically, the analysis was aimed at identifying what variables were contributing to increased retention aid use and wet end instability. Several models were developed using data sets with up to 88 process variables and over 3000 observations. It was found that increased retention aid use was driven primarily by PCC and TMP usage as well as the addition of Alaskan White Spruce to the TMP furnish.