• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.729-738
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• 2015

In this paper, we compare the robustness to the assumption of normality of the single control charts to control the mean and variance simultaneously. The charts examined were semicircle control chart, max chart and MSE chart with Shewhart individuals control charts. Their in-control and out-of-control performance were studied by simulation combined with computation. We calculated false alarm rate to compare among single charts by changing subgroup size and shifting mean of quality characteristics. It turns out that max chart is more robust than any of the others if the process is in-control. In some cases max chart and MSE chart are more robust than others if the process is out-of-control.

• Proceedings of the Safety Management and Science Conference
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• 2013.04a
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• pp.533-546
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• 2013

이 논문은 미세공정변동에서 극소불량을 감지하는 관리도의 경제적 설계를 개발하기 위한 조사연구이다. 일반적인 관리도의 설계는 통계적 설계와 경제적 설계로 구분할 수 있다. 공정의 변동 원인에 따라 샘플의 간격(h), 샘플의 크기(n), 관리한계선(k) 등의 설계 모수를 최적접근방법으로 결정을 하는 경제적 설계의 모델을 조사하였다. 관리도의 경제적 설계는 공정의 관리이상상태를 효율적으로 감지하여 관리상태로 정상화 시키는 것에 대한 공정의 개선비용과 기대품질비용을 절약 할 수 있는 최적설계 방안이다. 그리고 Shewhart 관리도의 X-bar 통계량으로 극소불량을 검출 하는것에 한계가 있기 때문에 Zp 통계량과 분포를 설계하여 극소불량을 빠르게 감지할 수 있는 Zp 관리도의 설계를 적용하고, 미세공정변동을 정확하게 감지할 수 있는 CUSUM 관리도를 동시에 적용하였다. 따라서, 미세공정변동과 극소불량을 동시에 관리 할 수 있는 Zp-CUSUM 관리도의 통계적 설계 구조를 체계화 하였으며, 기존의 경제적 설계의 모델을 비교 분석하여 새로운 경제적 설계에 대한 모델을 제안하고자 한다.

• Journal of the Korea Safety Management & Science
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• v.12 no.4
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• pp.255-263
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• 2010

The research developes short-run standardized control charts(SSCC) and short-run acceptance control charts(SACC) under the various demand patterns. The demand patterns considered in this paper are three types such as high-variety and repetitive low-volume pattern, extremely-high-variety and nonrepetitive low-volume pattern, and high-variety and extremely-low-volume pattern. The short-run standardized control charts developed by extending the long-run ${\bar{x}}$-R, ${\bar{x}}$-s and I-MR charts have strengths for practioners to understand and use easily. Moreover, the short-range acceptance control charts developed in the study can be efficiently used through combining the functions of the inspection and control chart. The weighting schemes such as Shewhart, moving average (MA) and exponentially weighted moving average (EWMA) can be considered by the reliability of data sets. The two types according to the use of control chart are presented in the short-range standardized charts and acceptance control charts. Finally, process capability index(PCI) and process performance index(PPI) classified by the demand patterns are presented.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.999-1008
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• 2010

The objective of this paper is to develop variable sampling interval multivariate control charts that can offer significant performance improvements compared to standard fixed sampling rate multivariate control charts. Most research on multivariate control charts has concentrated on the problem of monitoring the process mean, but here we consider the problem of simultaneously monitoring both the mean and variability of the process.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.451-459
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• 2017

There are many researches showing that when a process change has occurred, variable sampling intervals (VSI) control chart is better than the fixed sampling interval (FSI) control chart in terms of reducing the required time to signal. When the process engineers use VSI control procedure, frequent switching between different sampling intervals can be a complicating factor. However, average number of samples to signal (ANSS), which is the amount of required samples to signal, and average time to signal (ATS) do not provide any control statistics about switching performances of VSI charts. In this study, we evaluate numerical switching performances of multivariate VSI EWMA chart including average number of switches to signal (ANSW) and average switching rate (ASWR). In addition, numerical study has been carried out to examine how to improve the performance of considered chart with accumulate-combine approach under several different smoothing constant and sample size. In conclusion, process engineers, who want to manage the correlation coefficients of related quality variables, are recommended to make sample size as large and smoothing constant as small as possible under permission of process conditions.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.519-530
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• 2015

The geometric chart has proven more effective than Shewhart p or np charts to monitor the proportion nonconforming in high-quality processes. Implementing a geometric chart commonly requires the assumption that the in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice in high-quality process where the proportion of nonconforming items is very small. Thus, the error in the parameter estimation increases and may lead to deterioration in the performance of the control chart if a sample size is inadequate. We suggest adjusting the control limits in order to improve the performance when a sample size is insufficient to estimate the parameter. We propose a linear function for the adjustment constant, which is a function of the sample size, the number of nonconforming items in a sample, and the false alarm rate. We also compare the performance of the geometric charts without and with adjustment using the expected value of the average run length (ARL) and the standard deviation of the ARL (SDARL).

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1487-1498
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• 2016

In monitoring a process, in-control process parameters must be estimated from the Phase I data. When we design the control chart based on the estimated process parameters, the control limits are usually chosen to satisfy a specific in-control average run length (ARL). However, as the run length distribution is skewed when the process is either in-control or out-of-control, the median run length (MRL) can be used as alternative measure instead of the ARL. In this paper, we evaluate the performance of Shewhart $\bar{X}$ chart with estimated parameters in terms of the average of median run length (AMRL) and the standard deviation of MRL (SDMRL) metrics. In simualtion study, the grand sample mean is used as a process mean estimator, and several competing process standard deviation estimators are used to evaluate the in-control performance for various amounts of Phase I data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.140-152
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• 2016

It is very important for the competitiveness and sustainable management of enterprises that the rapid changes in the managerial environments quickly and accurately are responded. For example, the large-scale investment accompanied by bad alternatives in accordance with misunderstanding of the managerial environments yields the huge cost and effort to modify and improve. In firm management, the quality of products and the productivity are influenced by changes of the endogenous factors yielded in manufacturing process and the exogenous factors as market, etc. These changes include not only changes in 4M (man, machine, material, method) but also those in the market, competitors, and technologies in the process of commodification, i.e., first, such disturbances make dispersion of the process big and odd. By Shewhart chart it can be checked that the process monitored is control-in or out. Business administration executes activities for input stabilization by monitoring changes in 4Ms, comparing with the standards, and taking measures for any abnormality. Second, TRM (technology road map) is to prospect product deployment and technological trend by predicting technologies in the competitive environment as the market, and to suggest the future directions of business. So, TRM must be modified and improved according to DR (design review) stages and changes in mass-production like input material change. Therefore, a role of TRM in input stabilization for reducing cost and man-hour is important. This study purposed to suggest that the environment changes are classified into endogenous factors and exogenous factors in production process, and then, quality and productivity should be stabilized efficiently through connection between TRM and input stabilization, and to prove that it is more effective for the display industry to connect TRM with input stabilization rather than to use TRM separately.

• Journal of radiological science and technology
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• v.39 no.4
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• pp.527-534
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• 2016

Dual-energy X-ray absorptiometry (DEXA) is the most widely used technical instrument for evaluating bone mineral content (BMC) and density (BMD) in patients of all ages. In 2016, DEXA devices operating is 5617 in Korea. In this study we investigated the quality of management practices survey for DEXA equipment and we analyzed it. We got a survey response rate of 12.6%. Accurate bone densitometry test is used data for estimation a patient's risk of fracture. However, improper bone densitometry will increase the possibility of causing a false positive. Therefore. it is essential to use the proper aids accurate bone densitomenty to be performed, and the quality control of the device to reduce the error factor of the tester through the training to reduce error for the device and the attitude.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.75-81
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• 2005

Borror et al. discussed the EWMA(Exponentially Weighted Moving Average) chart to monitor the count of defects which follows the Poisson distribution, referred to the $EWMA_c$ chart, as an alternative Shewhart c chart. In the $EWMA_c$ chart, the Markov chain approach is used to calculate the ARL (Average Run Length). On the other hand, in order to monitor the process fraction defectives P in high-yield processes, Xie et al. presented the CCC(Cumulative Count of Conforming)-r chart of which quality characteristic is the cumulative count of conforming item inspected until observing $r({\geq}2)$ nonconforming items. Furthermore, Ohta and Kusukawa presented the $CS(Confirmation Sample)_{CCC-r}$ chart as an alternative of the CCC-r chart. As a more superior chart in high-yield processes, in this paper we present an $EWMA_{CCC-r}$ chart to detect more sensitively small or moderate shifts in P than the $CS_{CCC-r}$ chart. The proposed $EWMA_{CCC-r}$ chart can be constructed by applying the designing method of the $EWMA_C$ chart to the CCC-r chart. ANOS(Average Number of Observations to Signal) of the proposed chart is compared with that of the $CS_{CCC-r}$ chart through computer simulation. It is demonstrated from numerical examples that the performance of proposed chart is more superior to the $CS_{CCC-r}$ chart.