• 품질경영학회지
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• 제24권3호
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• pp.145-159
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• 1996

In today's organization, measurement plays a crucial role in helping improve process or quality. In this paper, we review the measurement error study, classical gauge repeatability and reproducibility study, and designed experiment suited for the determination of the measurement capability. Measurement error study is very simple to use but is rather crude. Hence, it should be used as a preliminary study to determine whether further study is necessary. Classical gauge repeatability and reproducibility (GR&R) study is the most common technique for evaluation of gauge capability. It calculates a percentage that relates the repeatability, reproducibility, and overall R&R to the specification range for the parameter measured. Hence, the individual repeatability and reproducibility statistics will indicate the area on which to concentrate. However, GR&R study only gives a point estimate of each component, which leaves a room for improvement. It is always good to integrate the use of control charts to ascertain the statistical stability of the measurement process. The tools of statistical experimental design are available for a comprehensive design and analysis of the measurement process. Hence, in this paper, we present gauge capability analysis as an experimental design problem and compare it with the classical GR&R study.

• 대한임상검사과학회지
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• 제36권1호
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• pp.19-26
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• 2004

According to increase of domestic blood components use, the quality control of blood components is necessary to support good products. The purpose of this study is used to provide the producing index of the good product as compared with the accuracy and validity for the distribution of the quality control data. The value of mean, standard deviation, 95% confidence interval and degree of normal distribution of data were calculated by univariate procedure, the value of monthly mean of each blood centers per items were compared by Analysis of Variance(ANOVA) test for the degree of distribution. When there was difference among the mean values, the Duncan's multiple range test was done to confirm the difference. Finally, methods for accessing accuracy and validity of the quality data was done by the Contingency table test. The quality data of five blood centers was showed to the normal distribution and it was in a acceptable range. For each blood centers, the monthly means of Hematocrit(Hct), Platelet(PLT) and pH were not significantly different except Hct of C center, PLT of B, D center and pH of A center. The quality data per items was graded according to quality to six level. As a result of the comparative analysis, the monthly means of Hct of C and E center was significantly different higher than that of D, B and A center. The monthly means of PLT of A center and pH of C center was significantly different higher than that of the others. In the accuracy and validity of the quality control data, C center for Hct, A center for PLT and C center for pH were better than the other. The C blood center was most satisfiable and stable in the quality control for blood component. If the quality control method used in C blood center is adopted in other blood centers, the prepared level of the blood component of the center will be improved partly.

• 산업경영시스템학회지
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• 제36권2호
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• pp.56-62
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• 2013

Control chart is representative tool of Statistical Process Control (SPC). But, it is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In order to manage the process, we should consider not only stability of the variation also produce products with a high degree of matching the target value that is most ideal quality characteristics. There is a need for process control in consideration of economic loss. In this paper, we design a new control chart using the quadratic loss function of Taguchi. And we demonstrate effectiveness of new control chart by compare its ARL with ${\overline{x}}-R$ control chart.

• Industrial Engineering and Management Systems
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• 제8권3호
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• pp.139-147
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• 2009

Control charts are used to distinguish between chance and assignable causes in the variability of quality characteristics. When a control chart signals that an assignable cause is present, process engineers must initiate a search for the assignable cause of the process disturbance. Identifying the time of a process change could lead to simplifying the search for the assignable cause and less process down time, as well as help to reduce the probability of incorrectly identifying the assignable cause. The change point estimation by likelihood theory and the built-in change point estimation in a control chart have been discussed until now. In this article, we discuss two kinds of process change point estimation when the CUSUM ($\bar{x}$, s) control chart for monitoring process mean and variance simultaneously is operated. Throughout some numerical experiments about the performance of the change point estimation, the change point estimation techniques in the CUSUM ($\bar{x}$, s) control chart are considered.

• 제어로봇시스템학회논문지
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• 제22권4호
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• pp.276-280
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• 2016

Due to the increasing interest in safety and consistent product quality over a past few decades, demand for effective quality monitoring and safe operation in the modern industry has propelled research into statistical based fault detection and diagnosis methods. This paper describes the application of Hotelling $T^2$ index based Principal Component Analysis (PCA) method for fault detection and diagnosis in industrial processes. Multivariate statistical process control techniques are now widely used for performance monitoring and fault detection. Conventional methods such as PCA are suitable only for steady state processes. These conventional projection methods causes false alarms or missing data for the systems with transient values of processes. These issues significantly compromise the reliability of the monitoring systems. In this paper, a reliable method is used to overcome false alarms occur due to varying process conditions and missing data problems in transient states. This monitoring method is implemented and validated experimentally along with matlab. Experimental results proved the credibility of this fault detection method for both the steady state and transient operations.

• 한국의료질향상학회지
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• 제26권2호
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• pp.86-94
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• 2020

Purpose: This study aimed to identify current quality control (QC) practices of primary care clinics participating in the National Cancer Screening Program (NCSP) in Korea. Methods: A nationwide survey using a structured questionnaire was conducted among the primary care clinics participating in the NCSP, which were selected by a proportionate stratified sampling. The questionnaire consisted of general information about the responding clinics and the scope of QC activities undertaken. A total of 360 clinics responded and the set of data was then analyzed with Chi-square test and multivariable logistic regression analysis. Results: Among 360 respondents, 332 (92%) reported that they were involved in the QC activities. Most frequently performed QC activities were 'maintenance of facility and instruments' (89%) and 'staff training' (85%). The analysis revealed, with statistical significance (p<.05), that there was an association between certain characteristics of the clinics and the scope of QC activities. These findings also indicated that the diversity of QC practices varies according to the size of the clinics. The clinics screening more types of cancer, those with more screenees, and those with more employees were more likely to implement various QC activities including 'maintenance of facility and instruments', 'external quality control', and 'management of screening data'. Conclusion: To our knowledge, this is the first study to investigate the current status of QC activities conducted among primary care clinics participating in the NCSP. The results of this survey can be used as a basis for further development of policies on quality management of small- and medium-sized primary care clinics in Korea. However, further studies encompassing various aspects of QC activities and management of primary care clinics are needed to assess the current situation in a concise manner.

• 산업경영시스템학회지
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• 제39권3호
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• pp.10-17
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• 2016

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally ${\bar{x}}-R$ control chart or ${\bar{x}}-s$ control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

• 산업경영시스템학회지
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• 제26권3호
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• pp.39-49
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• 2003

Statistical process cintrol is intended to assist operators of a stable system in monitoring whether a change has occurred in the process, and it uses several control charts as main tools. In design and use of control chart, it is rational that probability of false alarm is minimized in stable process and probability of detecting shifts is maximized in out-of-control. In this study, we establish bootstrap control limits for robust M-estimator chart by applying the bootstrap method, called resampling, which could not demand assumptions about pre-distribution when the process is skewed and/or the normality assumption is doubt. The results obtained in this study are summarized as follows : bootstrap M-estimator control chart is developed for applying bootstrap method to M-estimator chart, which is more robust to keep ARL when process contain contaminate quality characteristic.

• 품질경영학회지
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• 제40권4호
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• pp.467-480
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• 2012

Purpose: This paper introduces new 2-of-3 main and supplementary runs rules to increase the performance of the classical $\bar{X}$ control chart for detecting small process shifts. Methods: The proposed runs rules are compared with other competitive runs rules by numerical experiments. Nonlinear optimization problem to minimize the out-of-control ARL at a specified shift of process mean for determining action and warning limits at a time is formulated and a procedure to find two limits is illustrated with a numerical example. Results: The proposed 2-of-3 main and supplementary runs rules demonstrate an improved performance over other runs rules in detecting a sudden shift of process mean by simultaneous changes of mean and standard deviation. Conclusion: To increase the performance in the detection of small to moderate shifts, the proposed runs rules will be used with $\bar{X}$ control charts.

• 환경영향평가
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• 제20권1호
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• pp.71-78
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• 2011

This paper aims to assessing impact of reduction of non-point source pollution in the Bokha Stream watershed. The BASINS/HSPF model was calibrated and verified for water flow and water qualities using Total Maximum Daily Load 8days data from 2006 to 2007. Accuracy of the BASINS/HSPF models in simulating hydrology and water quality was compared and there were somewhat differences of statistical results, but water flow and water quality were simulated in good conditions over the study period. The applicability of models was tested to evaluate non-point source control scenarios to response hydrology and water quality in the Bokha stream using various measures which include BMPs approach and change of landuse. The evaluation of reduction of non-point source pollution was developed using load-duration curve. Despite strong reduction of non-point source, there are not satiated target quality at low flow season.