• Journal of Korean Society for Quality Management
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• v.38 no.2
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• pp.190-201
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• 2010

This research proposes a method for designing VSI (Variable Sampling Interval) control charts with supplementary run rules. The basic idea is to apply various run rules and the VSI scheme to a control chart in order to increase the sensitivity. The sampling process of the VSI run rules chart is constructed by Markov chain approach. A procedure for designing the VSI run rules chart is proposed based on Lorenzen and Vance's model. Sensitivity study shows that the VSI run rules charts outperform the FSI (Fixed Sampling Interval) run rules charts for wide range of process mean shifts. A major advantage of the VSI run rules chart over other charts such as CUSUM, EWMA, and adaptive charts is it's simplicity in implementation. Some useful guidelines are proposed based on the sensitivity study.

• KIEAE Journal
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• v.4 no.3
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• pp.153-160
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• 2004

It is essential to know climatic characteristics of the site for energy efficient building design. However, it is difficult to obtain a climate data. Even though the climate data is obtained, it is difficult to be applied to the building design since it is usually consisted of just series of numbers. Also, designers cannot know the effective climatic design strategies suitable for the site with ease. Thus, this study aims to develope the climatic design tool working on the personal computer operated by windows 95/98/2000/XP. WYEC weather data and building bioclimatic chart are adopted for the climate analysis. Climatic Characteristics(distributions of the dominant factors, bioclimatic needs, needs to each passive design strategy, and the order of priority, etc.) of Seoul are analysed and presented as an example. Also, passive climatic design process making use of this tool is presented.

• Journal of Korean Ophthalmic Optics Society
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• v.5 no.2
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• pp.49-53
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• 2000

Comparing to an Image test chart which printed from computer. Hahn's standard test chart and Chart project test chart propose to make the program of an image test chart in computer. Test type of the test chart should be programed by difference size which was examined Hangul program of Hangul & Computer Co. An image test of visual acuity most decreased among 3 kinds of testing. Testing of Fixation disparity was same between Diplopia test and chart project test chart, so that. Design of test chart could be programed diverse by Hangul program of Hangul & Computer Co.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.31-39
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• 1993

This paper considers a procedure for the economic design of a cumulative score(CUSCORE) control chart and more sensitive than X-type control chart for small shift to control the mean of a process with a exponentially distributed quality characteristic. An expected loss - cost model as a function of design variables(sample size, sampling interval, scoring limit and decision limit) is derived. Direct search techniques are used to optimize the model subject to ARL in control. Numerical examples and sensitivity analysis of the model are presented. For selected values of situation parameters a comparison study with CUSUM charts is given. CUSCORE control charts compare favourably with CUSUM charts in cost for speedy production process. The proposed control chart can be directly applied for controlling the lifetime characteristics.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.29-39
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• 2009

This article investigates economic-statistical design of VSSI(variable sampling size and interval) cause-selecting charts considering two assignable causes. We consider a process which is composed of two dependent sub-processes. In each sub-process, two kinds of assignable cause may exist. We propose a procedure for designing VSSI cause-selecting charts, based on Lorenzen and Vance model. Computational experiments show that the VSSI cause-selecting chart is superior to the FSSI cause-selecting chart in the economic-statistical characteristics, even under two assignable causes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.55-63
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• 1999

Past studies on economic control charts for controlling process means assumed that the measures of a quality characteristic do not have measurement error. In practice, however, this assumption is frequently violated. In this paper, the economic design models of three control charts(Xbar control chart, Xbar control chart with warning limits, and CUSUM control chart) for controlling process means are developed on the assumption that the measures can have measurement error. The effects of measurement error on the process control cost and design parameters of three economic control charts are examined. According to the experiments done in this study, when measurement error exists, the economic CUSUM control chart has lower process control cost in comparison with two other control charts. When measurement error becomes larger, both the sample size and the sampling interval increase while the control limits decrease.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.327-336
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• 2012

Purpose: In this study, we research the hurdle rate method to suggest the robust control chart for a contaminated process less vulnerable to fault values than existing control charts. Methods: We produce the results of p, ARL values to compare the performance of two control charts, $\bar{x}-s$ that has been used typically and TM-TS that is suggested by this paper. We implement the simulation focusing on three cases, change of deviation, mean and both of them. Results: We draw a conclusion that the TM-TS control chart has better efficiency than $\bar{x}-s$ control chart over the three cases. Conclusion: We insist that applying TM-TS control chart for a polluted process is more effective than $\bar{x}-s$ control chart.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.97-103
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• 2006

Recently, the control chart is developed for monitoring processes with normal short production runs by the coefficient of variation(CV) characteristic for a normal distribution. This control chart does not work well in non-normal short production runs. And most of industrial processes are known to follow the non-normal distribution. Therefore, the control chart is required to be developed for monitoring the processes with non-normal short production runs by the CV characteristics for a non-normal distribution. In this paper, we suggest the control chart for monitoring the processes with a gamma short runs by the CV characteristics for a gamma distribution. This control chart is denoted by the gamma CV control chart. Futhermore evaluated the performance of the gamma CV control chart by average run length(ARL).

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.156-168
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• 2004

This research investigates the statistical efficiency of variable sampling size & sampling interval(VSSI) $\bar{X}$ charts under two assignable causes. Algorithms for calculating the average run length(ARL) and average time to signal(ATS) of the VSSI $\bar{X}$ chart are proposed by employing Markov chain method. States of the process are defined according to the process characteristics after the occurrence of an assignable cause. Transition probabilities are carefully derived from the state definition. Statistical properties of the proposed chart are also investigated. A simple procedure for designing the proposed chart is presented based on the properties. Extensive sensitivity analyses show that the VSSI $\bar{X}$ chart is superior to the VSS or VSI $\bar{X}$ chart as well as to the Shewhart $\bar{X}$ chart in statistical sense, even tinder two assignable causes.

• Journal of Korean Society for Quality Management
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• v.33 no.3
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• pp.126-134
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• 2005

This paper proposes a selectively cumulative sum(S-CUSUM) control chart for detecting shifts in the process mean. The basic idea of the S-CUSUM chart is to accumulate previous samples selectively in order to increase the sensitivity. The S-CUSUM chart employs a threshold limit to determine whether to accumulate previous samples or not. Consecutive samples with control statistics out of the threshold limit are to be accumulated to calculate a standardized control statistic. If the control statistic falls within the threshold limit, only the next sample is to be used. During the whole sampling process, the S-CUSUM chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L -consecutive control statistics fall outside the threshold limit. The number L is a decision variable and is called a 'control length'. A Markov chain approach is employed to describe the S-CUSUM sampling process. Formulae for the steady state probabilities and the Average Run Length(ARL) during an in-control state are derived in closed forms. Some properties useful for designing statistical parameters are also derived and a statistical design procedure for the S-CUSUM chart is proposed. Comparative studies show that the proposed S-CUSUM chart is uniformly superior to the CUSUM chart or the Exponentially Weighted Moving Average(EWMA) chart with respect to the ARL performance.