• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.741-747
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• 2009

Properties of multivariate Shewhart and EWMA (Exponentially Weighted Moving Average) control charts for monitoring variance-covariance matrix of quality variables are investigated. Performances of the proposed charts are evaluated for matched fixed sampling interval (FSI) and variable sampling interval (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 charts are also investigated.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.151-159
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• 2004

Properties of the variable sampling interval(VSI) control charts 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 charts are also investigated.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.126-135
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• 2003

A basic assumption in standard applications of control charts is that the observations are statistically independent. However, this assumption is often violated from processes in many industries. The presence of autocorrelation has a serious impact on the performance of control charts, causing a dramatic increase in the frequency of false alarms. This paper considers a process in which the observations can be modeled as a first order autoregressive(AR(1)) process, and develops (equation omitted) charts with the variable sample size(VSS) scheme for monitoring the mean of this process.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.819-829
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• 2010

Properties of multivariate variable sampling interval (VSI) Shewhart and CUSUM charts for monitoring mean vector of related quality variables are investigated. To evaluate average time to signal (ATS) and average number of switches (ANSW) of the proposed charts, Markov chain approaches and simulations are applied. Performances of the proposed charts are also investigated both when the process is in-control and when it is out-of-control.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.429-440
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• 2003

Variable sampling rate (VSR) control charts vary the sampling interval and/or the sample size according to value of the control statistic. It is known that $\bar{X}$ charts with VSR scheme lead to large improvements in performance over those with fixed sampling rate (FSR) scheme. In this paper, we studied $\bar{X}$ charts with several VSR schemes, and compared their statistical performance each other.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.127-133
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• 2001

In this article we establish multivariate cumulative sum (CUSUM) control charts based on residual vector with correlated observations. We first find the residual vector and its expectation and variance-covariance matrix and then evaluate the average run length (ARL) of the control charts.

• Journal of Korean Society for Quality Management
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• v.24 no.3
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• pp.65-76
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• 1996

This paper is concerned with designing $\bar{X}$-control charts when an estimate error may be Inevitable. Estimate error offen can not be avoided in estimating or measuring the parameter values of the cost model for the control charts. The bounded interval is a common practice to compensate for inherent estimating error. We introduce the 'propagation of error technique to deal with the economic design of the $\bar{X}$-control charts with imprecise information on the cost model parameters. A numerical example is presented to show· its ability in the economic design of $\bar{X}$-control charts.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.50-60
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• 1998

This paper is concerned with the design of two residual control charts for real-time monitoring of the continuous flow processes. Two different control charts are designed under the situation that observations are correlated each other. Kalman-Filter based model estimation is employed when the process model is known. A black-box approach, based on Back-Propagation Neural Network, is also applied for the design of control chart when there is no prior information of process model. Performance of the designed control charts and traditional control charts is evaluated. Average run length(ARL) is adopted as a criterion for comparison. Experimental results show that the designed control chart using the Neural Network's modeling has shorter ARL than that of the other control charts when process mean is shifted. This means that the designed control chart detects the out-of-control state of the process faster than the others. The designed control chart using the Kalman-Filter based model estimation also has better performance than traditional control chart when process is out-of-control state.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.7-14
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• 2004

In this paper, we present an effective method for process control using the Demerit-EWMA control chart in the process where nonconforming units or nonconformities are occurred by various types. We compare performance of Demerit control chart, Demerit-CUSUM control chart and Demerit-EWMA control chart based on the average run length.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.431-439
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• 2004

In this paper, we present an effective method for process control using the Demerit-EWMA control chart in the process where nonconforming units or nonconformities are occurred by various types. We compare performance of Demerit control chart, Demerit-CUSUM control chart and Demerit-EWMA control chart based on the average run length(ARL).