• 품질경영학회지
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• 제37권2호
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• pp.46-57
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• 2009

The traditional approach to economic design of control charts is based on the assumption that a process is monitored using a performance variable. However, various types of automatic test equipments recently introduced as a part of factory automation usually measure surrogate variables instead of performance variables that are costly to measure. In this article we propose a model for economic design of a control chart which uses a surrogate variable that is highly correlated with the performance variable. The optimum values of the design parameters are determined by maximizing the total average income per cycle time. Numerical studies are performed to compare the proposed $\bar{X}$ control charts with the traditional model using the examples in Panagos et al. (1985).

• Communications for Statistical Applications and Methods
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• 제14권2호
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• pp.365-376
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• 2007

This research considers to propose the control charts using median for the location parameter. In order to decide the control limits, we apply several bootstrap methods through the approach obtaining the confidence interval except the standard bootstrap method. Then we illustrate our procedure using an example and compare the performance among the various bootstrap methods by obtaining the length between control limits through the simulation study. The standard bootstrap may be apt to yield shortest length while the bootstrap-t method, the longest one. Finally we comment briefly about some specific features as concluding remarks.

• 산업경영시스템학회지
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• 제20권43호
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• pp.205-209
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• 1997

One objective of the u control chart is to detect changes of mean nonconformities per unit occurred owing to various causes. This paper shows the detection probability using the Poisson distribution for various parameters, that is, subsample size n, mean nonconformities per unit $u_o$, and $u_o's$ change ratio k. We find that (1) as $u_o$ increases the smaller n is required for the same detection probability and the same change ratio; (2) as k gets away from 1 the smaller n is required; (3) the bigger n is required for the bigger detection probability. Several tables are given from our findings and are hoped to be used as guidelines for u chart users.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.289-301
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• 2003

In this paper, we propose Shewhart control chart and EWMA control chart using the autocorrelated data which are common in chemical and process industries and lead to increase the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and simulation is conducted to investigate the performances of the proposed control charts.

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.21-29
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• 2002

Several different control statistics to simultaneously monitor dispersion matrix of several quality variables are presented since different control statistics can be used to describe variability. Multivariare cumulative sum (CUSUM) control charts are proposed and the performances of the proposed CUSUM charts are evaluated in terms of average run length (ARL). Multivariate Shewhart charts are also proposed to compare the properties of the proposed CUSUM charts. The numerical results show that multivariate CUSUM charts are more efficient than multivariate Shewhart charts for small or moderate shifts. And we also found that small reference value of the CUSUM chart is more efficient for small shift.

• Journal of the Korean Data and Information Science Society
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• 제11권2호
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• pp.217-223
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• 2000

In this paper, we develop optimal decision interval exponentially weighted moving average(EWMA) scheme for the process mean and the reciprocal measure of dispersion of the inverse Gaussian distribution.

• 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.

• Journal of the Korean Statistical Society
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• 제33권2호
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• pp.219-231
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• 2004

Process adjustment is a complimentary tool to process monitoring in process control. Although original intention of process adjustment is not identifying a special cause, detection and elimination of special causes may lead to significant process improvement. In this paper, we examine the impact of special causes on process adjustment. The bias in the adjusted output process is derived for each type of special causes, and average run length (ARL) of the Shewhart chart applied to the adjusted output is computed for each special cause types. Numerical results are illustrated for the ARL of the Shewhart chart, thereupon seriousness of special causes on process adjustment is evaluated for each type of special causes.

• 대한안전경영과학회지
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• 제10권2호
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• pp.205-210
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• 2008

The research interprets the principles of sampling error design for quality statistics models such as hypothesis test, interval estimation, control charts and acceptance sampling. Introducing the proper discussions of the design of significance level according to the use of hypothesis test, then it presents two methods to interpret significance by Neyman-Pearson and Fisher. Second point of the study proposes the design of confidence level for interval estimation by Bayesian confidence set, frequentist confidential set and fiducial interval. Third, the content also indicates the design of type I error and type II error considering both productivity and customer claim for control chart. Finally, the study reflects the design of producer's risk with operating charistictics curve, screening and switch rules for the purpose of purchasing and subcontraction.

• 품질경영학회지
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• 제24권2호
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• pp.172-178
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• 1996

In this study, we developed a software for statistical process control. This software presents $\bar{x}$, R, CUSUM, EWMA control chart and process capability index. In this system, statistical process control methods are integrated into the automated method on a real time base. It is available in process control of specified type and can be performed on personal computer with network system.