• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.403-420
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• 1994

An economic design of the $\bar{X}-R$ chart using variable sample size (VSS) scheme is proposed in this paper. In this design the sample size at each sampling time changes according to the values of the previous two sample statistics, sample mean and range. The VSS scheme uses large sample if the sample statistics appear near inside the control limits and smaller sample otherwise. The set of process parameters, such as the sampling interval, control limits and the sample sizes, are chosen to minimize the expected cost per hour. The efficiency of the VSS scheme is compared to the fixed sample size one for cases where there is multiple of assignable causes. Percent reductions of the expected cost in the VSS design are calculated for some given sets of cost parameters. It is shown that the VSS scheme improves the confidence of the procedure and performs statistically better in terms of the number of false alarms and the average time to signal, respectively.

• Journal of Korean Society for Quality Management
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• v.15 no.2
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• pp.10-19
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• 1987

Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the $\overline{X}$-chart, X-chart, $\widetilde{X}$-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In the Shewhart $\overline{X}$-chart, which is the most widely used one in Korea, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for the more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, and Truncated-normal distributions.

• Publications of The Korean Astronomical Society
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• v.28 no.3
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• pp.37-54
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• 2013

China and Korea have a long history of star charts, dating from the prehistoric period. Historically, Korean astronomy has been deeply influenced by China over the last two thousand years, particularly on constellation system. Therefore, Chinese and Korean traditional star charts have many similarities in terms of shape of constellation, number of star, and so forth. Korean star charts, however, have lots of unique characteristics distinguishing from Chinese ones, such as, size of star and position of constellation. Overall knowledge of the Chinese star chart is required to study the Korean star chart. In this paper, I focus on introducing selected star charts in China and Korea. Although this review is very limited, I hope that this paper is helpful in research in the field of historical astronomy.

• 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 for Quality Management
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• v.28 no.2
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• pp.70-88
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• 2000

Short runs where it is neither possible nor practical to obtain sufficient subgroups to estimate accurately the control limit are common in modem business environments. In this study, the standardized control chart, Hillier's exact method, Q chart, EWMA(Exponentially Weighted Moving Average) chart for Q statistics and EWMA chart for mean and absolute deviation among many SPC(Statistical Process Control) techniques for short runs have been reviewed and advantages and disadvantages of these techniques are discussed. The simulation experiments to compare performances of these variable charts for process mean and variations are conducted for combination of subgroup size, scale and timing of shifts of process mean an/or standard deviation. Based upon simulation results, some guidelines for practitioners to choose short run SPC techniques are recommended.

• 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.

• Korean Journal of Human Ecology
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• v.14 no.1
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• pp.107-117
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• 2005

The purpose of this study is to develop the size and grading increments chart for the middle-aged obese women compared with normal women in middle age. Seven hundred and thirty three women's data from the 4th National Korean Size Survey for Standardization (1997) were analyzed. It was found that size increment of bust and hip girth of obese women was different from that of ordinary middle-aged women. The rate of coverage for a certain set of size specification and the grading increment value for the clothing of Korean obese women in middle aged group were also suggested. The relative percentage value of grading rule based on the change in bust girth increment of Korean obese women was quite different from that of American women. In conclusion, it was noted that the characteristics of the body size specification of obese women was quite different from those of the corresponding age group, so that the separated size specification and grading rule are needed to be used in the manufacturing process of obese women's clothing.

• Journal of the Korean Professional Engineers Association
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• v.20 no.3
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• pp.15-25
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• 1987

Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the X-chart, X-chart, X-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In Shewhart X-chart, which is the most widely used one in Korea, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for tile more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, Truncated-normal distributions. Robustness of the proposed median control chart is compared with that of the X-chart, the former tends to be superior to the latter as the probability distribution of the process becomes more skewed. The average run length to detect the assignable cause is also compared when the process has a Normal or a Gamma distribution for which the properties of X are easy to verify, the proposed chart is slightly worse than the X-chart for the normally distributed product but much better for Gamma-distributed products. Average Run Lengths of the other distributions are also computed. To use the proposed control chart, the probability distribution of the process should be known or estimated. If it is not possible, the results of comparison of the robustness force us to use the proposed median control chart based on a normal distribution. To estimate the distribution of the process, Sturge's formula is used to graph the histogram and the method of probability plotting, $X^2$-goodness of fit test and Kolmogorov-Smirnov test, are discussed with real case examples. A comparison of the propose4 median chart and the X chart was also performed with these examples and the median chart turned out to be superior to the X-chart.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.101-106
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• 1987

Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the $\bar{X}$-chart, $\bar{X}$-chart, $\bar{X}$-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In Shewhart $\bar{X}$-chart. which is the most widely used one in Kora, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for the more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, Truncated-normal distributions. Robustness of the proposed median control chart is compared with that of the $\bar{X}$-chart; the former tends to be superior to the latter as the probability distribution of the process becomes more skewed. The average run length to detect the assignable cause is also compared when the process has a Normal or a Gamma distribution for which the properties of X are easy to verify, the proposed chart is slightly worse than the $\bar{X}$-chart for the normally distributed product but much better for Gamma-distributed products. Average Run Lengths of the other distributions are also computed. To use the proposed control chart, the probability distribution of the process should be known or estimated. If it is not possible, the results of comparison of the robustness force us to use the proposed median control chart based oh a normal distribution. To estimate the distribution of the process, Sturge's formula is used to graph the histogram and the method of probability plotting, $\chi$$^2$-goodness of fit test and Kolmogorov-Smirnov test, are discussed with real case examples. A comparison of the proposed median chart and the $\bar{X}$ chart was also performed with these examples and the median chart turned out to be superior to the $\bar{X}$-chart.