• 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".

• 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.

• 품질경영학회지
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• 제39권2호
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• pp.234-243
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• 2011

Multivariate control charts are widely used to monitor the performance of a multivariate process over time to maintain control of the process. Although existing multivariate control charts provide control limits to monitor the process and detect any extraordinary events, it is a challenge to identify the causes of an out-of-control alarm when the number of process variables is large. Several fault identification methods have been developed to address this issue. However, these methods require a normality assumption of the process data. In the present study, we propose a bootstrapped-based $T^2$ decomposition technique that does not require any distributional assumption. A simulation study was conducted to examine the properties of the proposed fault identification method under various scenarios and compare it with the existing parametric $T^2$ decomposition method. The simulation results showed that the proposed method produced better results than the existing one, especially in nonnormal situations.

• Journal of the Korean Data and Information Science Society
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• 제24권6호
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• pp.1275-1283
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• 2013

다변량 통합공정관리의 기본절차는 잡음이 내재하는 공정에 수정조치를 취하여 공정편차벡터를 백색잡음벡터로 전환하도록 하여 공정제곱편차벡터를 최소화하게 되는 것이며, 이러한 다변량 통합공정관리의 수정활동을 하는 경우 공정에 이상원인이 발생하면 관리도를 통해 이를 탐지하고 제거하게 된다. 수정된 공정은 이상원인 발생 전에는 백색잡음이지만, 이상원인 발생 후 다양한 형태의 시계열 모형으로 변환하게 된다. 만약 수정된 공정을 탐지하여 이상원인의 신호가 발생한 경우 교정활동을 통하여 이를 제거해야 하지만, 구조적으로 교정이 불가능 하거나 교정활동의 비용이 많이 발생하는 경우에는 이상원인의 효과를 감안하여 수정활동을 재조정해야할 것이다. 이 논문에서는 공정모형으로 다변량 IMA(1,1)모형을 가정하고 다변량 통합공정관리 절차를 수행하는 경우 이상신호가 발생한 후 재수정 절차에서 필요한 모수추정을 하고자 한다.

• 대한산업공학회지
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• 제29권2호
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• pp.114-125
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• 2003

This paper proposes multivariate process capability indices (PCIs) for skewed populations using $T^2$rand modified process region approaches. The proposed methods are based on the multivariate version of a weighted standard deviation method which adjusts the variance-covariance matrix of quality characteristics and approximates the probability density function using several multivariate Journal distributions with the adjusted variance-covariance matrix. Performance of the proposed PCIs is investigated using Monte Carlo simulation, and finite sample properties of the estimators are studied by means of relative bias and mean square error.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.223-232
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• 1999

Multivariate quality control charts with combine-accumulate approach and accumulate-combine apprach for monitoring both means and variances under multivariate normal process are investigated. Numerical performances of the charts show that multivariate EWMA chart with accumulate-combine approach can be recommended for all kinds of shift in means and variances.

• 대한수학회지
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• 제39권1호
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• pp.119-126
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• 2002

For a stationary multivariate linear process of the form X$_{t}$ = (equation omitted), where {Z$_{t}$ : t = 0$\pm$1$\pm$2ㆍㆍㆍ} is a sequence of stationary linearly positive quadrant dependent m-dimensional random vectors with E(Z$_{t}$) = O and E∥Z$_{t}$∥ $^2$< $\infty$, we prove a central limit theorem.theorem.

• Journal of the Korean Statistical Society
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• 제32권1호
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• pp.11-20
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• 2003

Let｛Ｘt｝be an m-dimensional linear process of the form (equation omitted), where｛Zt｝is a sequence of stationary m-dimensional weakly associated random vectors with EZt = O and E∥Zt∥$^2$＜$\infty$. We Prove central limit theorems for multivariate linear processes generated by weakly associated random vectors. Our results also imply a functional central limit theorem.

• 호남수학학술지
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• 제27권3호
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• pp.505-513
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• 2005

The aim of this paper is to establish a functional central limit theorem for multivariate moving average process generated by negatively associated random vectors under the finite second moments.

• 통합자연과학논문집
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• 제9권3호
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• pp.215-222
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• 2016

When the linear correlation of the quality variables are considerably high, multivariate control charts may be a more effective way than univariate charts which operate quality variables and process parameters individually. Performances and efficiencies of the multivariate control charts under multivariate normal process has been considered. Some numerical results are presented under small scale of the shifts in the process to see the improvement of the efficiency of EWMA chart and CUSUM chart, which use past quality information, comparing to Shewart chart, which do not use quality information. We can know that the decision of the optimum value of the smoothing constant in EWMA structure or the reference value in CUSUM structure are very important whether we adopt combine-accumulate technique or accumulate-combine technique under the given condition of process.