• 산업경영시스템학회지
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• 제23권61호
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• pp.89-98
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• 2000

For statistical process control, the process data are collected by the measurement system. But, the measurement system may have instrument error or/and operator error. In the measured values of products, the total observed variance consists of process variance and variance due to error of measurement system. In this paper, we design more practical T-s control chart considering estimated measurement error The effects of measurement error on the expected total cost and design parameters are investigated.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2008년도 춘계학술대회
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• pp.283-293
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• 2008

Analysis of Means(ANOM) is a visualization tool for comparing several means to the grand mean like control chart type. This paper reviews five ANOM methods for continuous data such as ANOM, ANOME (ANOM for Treatment Effects), ANCON (Analysis of Contrasts), ANOMV (ANOM for Variance), ANOMC (ANOM for Correaltion). Three ANOM tools for discrete data such as ANOMNP (ANOM for Nonconforming Proportions), ANOMNC (ANOM for Nonconforming Unit), ANOMNPU (ANOM for Nonconfirmities Per Unit) are also developed.

• 산업경영시스템학회지
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• 제26권4호
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• pp.12-22
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• 2003

The purposes of this study are to investigate the conformity of Korean Standards(KS) according to agreement on WTO/TBT, and to propose systematic frameworks of preparation, adoption, and application for KS in our enterprises. Significant changes in this establishment, revision, and abrogation include the following divisions; i) statistics-vocabulary and symbols, ii) Shewhart control chart, iii) statistical interpretation of data, iv) sampling procedures for inspection by attributes, v) sequential sampling plans for inspection.

• 대한산업공학회지
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• 제41권6호
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• pp.521-529
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• 2015

Statistical process control techniques have been greatly implemented in industries for improving product quality and saving production costs. As a primary tool among these techniques, control charts are widely used to detect the occurrence of assignable causes. In most works on the control charts it considered the problem of monitoring the mean and variance, and the quality characteristic of interest is normally distributed. In some situations monitoring of the minimum and maximum values is more important and the quality characteristic of interest is the Weibull distribution rather than a normal distribution. In this paper, we consider the statistical design of minimum and maximum control charts when the distribution of the quality characteristic of interest is Weibull. The proposed minimum and maximum control charts are applied to the wind data. The results of the application show that the proposed method is more effective than traditional methods.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.767-771
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• 2002

This paper proposes a multivariate $T^2$ variable interval control chart with sampling at fixed times, where samples are taken at specified equally spared fixed time points, and additional samples are allowed between these fixed times when indicated by the preceding $T^2$ statistics. At fixed sampling tunes, the $T^2$ statistics are composed of all quality characteristics, and a part of qualify characteristics are selected to obtain $T^2$ statistics at additional sampling times. A Markov chain approach is used to evaluate the performance of the proposed chart.

• 한국경영과학회지
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• 제20권3호
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• pp.123-146
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• 1995

Several quality control schemes have been extensively compared using multivariate normal data sets simulated with various correlation structures. They include multiple univariate CUSUM charts, multivariate EWMA charts, multivariate CUSUM charts and Shewhart T$^{3}$ chart. This paper considers a new approach of the multivariate EWMA chart, in which the smoothing matrix has full elements instead of only diagonal elements. Performance of the schemes is measured by avaerage run length (ARL), coefficient of variation of run length (CVRL) and rank in order of signaling of off-target shifts in the process mean vector. The schemes are also compared by noncentrality parameter. The multiple univariate CUSUM charts are generally affected by the correlation structure. The multivariate EWMA charts provide better ARL performance. Especially, the new EWMA chart shows remarkable results in small shifts.

• 조명전기설비학회논문지
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• 제12권2호
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• pp.54-61
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• 1998

PLC를 사용한 공정제어시스템의 설계에서 PLC 표준언어중 LD 언어가 가장 널리 사용되고 있다. 그러나 LD 언어는 데이터처리와 유지보수에 대한 단점이 있다. 반면에 SFC 그래픽언어는 복잡한 순차동작을 간결하게 記述할 수 있는 완벽한 방법이지만, 인터록조건을 記述하는데 문제점이 있다. 본 논문에서는 기존의 SFC 컴파일러를 사용하여 인터록을 실현하는 방법을 제시하고, 실예로서 In-Line Spin Coater에 적용하여 타당성을 확인하였다.

• 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.

• 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.

• Food Science and Biotechnology
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• 제18권3호
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• pp.745-748
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• 2009

Sensory quality variations of jajang sauce were monitored by the $\bar{X}-chart$ and capability analysis based on specifications of each sensory attributes. For sensory quality control (QC) of the sauce which has a strong sweetness and sourness, the ratio of sourness/sweetness was examined as a necessary QC factor to maintain the balance of sweetness and sourness. For the sensory QC factors, all the sensory data were divided into individual sensory score of reference which was a pack of sauce manufactured a week ago. The ratio form of sensory data was useful for decreasing individual variations and for increasing normality of data measured by category scale. The overall proportion of out-spec products under normal manufacturing conditions was obtained by capability analysis of sensory data with normal distribution. Out-spec samples were monitored by the $\bar{X}-chart$ of each sensory attributes.