• Journal of Korean Society for Quality Management
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• v.11 no.1
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• pp.44-50
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• 1983

The main factors of determining the Control Line of the Control Chart can be classified as follows: 1) sample size (n), 2) the factor that determines the spread of Control Limits (B), (3) sampling frequency (h). The determination of these factors can be explained according to the extent that occurrences of assignable cause should be detected. The purpose of this paper are two: one is for composing a model of which use should be designated for economic decision on the size of these factors leading to the Control Line of the Control Chart, the other is about what influence increasing or decreasing condition, according to changeability of the size of these factors, of expect cost can have on the economy when the Control Chart is used.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.252-264
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• 2004

Variable sampling Interval (VSI) control charts vary the sampling interval according to value of the control statistic while the sample size is fixed. It is known that control charts with 2-state VSI scheme, which uses only two sampling intervals, give good statistical properties. Variable sample size (VSS) control charts vary the sample size according to value of the control statistic while the sampling interval is fixed. In the VSS scheme no optimal results are known for the number of sample sizes. It is also known that the variable sampling rate (VSR) $\bar{X}$ control chart with 2-state VSS and 2-state VSI scheme leads to large improvements In performance over the fixed sampling rate (FSR) $\bar{X}$ chart, but the optimal number of states for sample size Is not known. In this paper, the VSR Χ charts with multi-state VSS and 2-state VSI scheme are designed and compared to 2-state VSS and 2-state VSI scheme. The multi-state VSS scheme is considered to, achieve an additional improvement by switching from the 2-state VSS scheme. On the other hand, the multi-state VSI scheme is not considered because the 2-state scheme is known to be optimal. The 3-state VSS scheme improves substantially the sensitivity of the $\bar{X}$ chart especially for small and moderate mean shifts.

• Journal of Korean Society for Quality Management
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• v.14 no.2
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• pp.2-8
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• 1986

This thesis is concerned with the design of control chart based on the sample median which is easy to use in practical situations and to analyze the properties for non-normally distributed Weibull process. In this cases are use to the quality characteristics of the process are not normally distributed but skewed due to the intermitted production, small lot size and sample size is small one n=3 or n=5, etc. And when it relates unsymmetrically distributed process, model designed median control chart is more effective than Shewhart $\bar{x}$-chart which assumed on normal distribution, when we exactly should be known Weibull distribution or estimated. The median control chart in this thesis is more robustness compared with other conventionally developed control chart.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.1-14
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• 2005

We propose a VSSI-CRL(Variable Sampling Size and Samplina Interval-Conforming Run length) synthetic control chart in order to improve the statistical characteristics of both the VSSI chart and the CRL synthetic chart. The VSSI-CRL chart utilizes VSSI sampling scheme, but it produces a signal only when the CRI is less than a given limit. An algorithm for calculating the ARL(Average Run length) and ATS(Average Time to Signal) of the VSSI-CRL chart is developed by employing Markov chain method. We present some lemmas for describing the statistical characteristics of the VSSI-CRL chart under in-control state. A procedure for designing the VSSI-CRL chart is proposed based on the lemmas. Extensive comparative studios show that the VSSI-CRL chart is superior to the CRL synthetic chart or the VSSI chart in general, and is comparable to the EWMA chart in ATS performance.

• The Research Journal of the Costume Culture
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• v.3 no.2
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• pp.307-321
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• 1995

The purpose of this study is to make the size chart of the child's ready-made upper garnet. For his study, we used the 1992 national anthropometric database. The results obtained are as follows. (1) It is known that the bust girth-based size chart is better than the age-based one. (2) The size range of the bust girth was 55∼73 cm to the size of the child's upper garment, and the number of the size was 7. Then the cover-rate was 86%. (3) In this study, the unisex chart was newly made because it was hardly difficult to find the actual size difference between boys and girls.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.114-122
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• 2004

In statistical process control applications, variable sample size (VSS) $\bar{X}$ chart is often used to detect the assignable cause quickly. However, it is usually assumed that only one assignable cause results in the out-of-control in the process. In this paper, we propose the algorithm to minimize the function of cost per unit time and compare the economic design and the statistical design by use of the value of cost per unit time. We consider double assignable causes to occur with compound in the process and adopt the Markov chain approach to investigate the statistical properties of VSS $\bar{X}$ chart. A procedure that can calculate the control chart's parameters is proposed by the economic design.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.4
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• pp.549-554
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• 2013

Purpose: To determine the minimal illumination for visual acuity with the decimal vision chart and individual difference with varying contrast and illumination. Methods: Landolt's vision chart with 10 different grade of contrast was made. Minimal illumination was measured for 69 eyes using 100% contrast vision chart. Minimal contrast for identifying the chart was measured in conditions of the minimal illumination and 230 lx, respectively. Results: Minimal illumination was gradually increased with decrease of the chart size. Mean of minimal illumination to identify the 1.0 visual acuity was $74.39{\pm}25.90$ lx with range of 17~107 lx. In conditions of the minimal illumination and 230 lx, the minimal contrast for identifying the chart were gradually increased with decrease of the chart size in both conditions, the those deviation for 69 eyes was also increased. Conclusions: For refractive correction, examiners need to consider the individual difference for identifying the visual chart according to illumination and contrast.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.132-141
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• 2003

As the technology has improved and demands of customers have varied, a lot of products are getting diverse and intricate. Consequently, the enterprise that produce products have to simultaneously consider the various variables for the very products. There are some scheme, such as Multivariate control chart and Demerit control chart, designed to simultaneously monitor the variables in the process. In this paper, we present an effective method for process control using the Demerit-CUSUM control chart in the process where nonconforming units or nonconformities are occured by various types. In addition, we show interpretation method for abnormal signal in order to quickly detect the assignable causes as Demerit-CUSUM control chart signals abnormality. we compare performance of Demerit control chart and Demerit-CUSUM control chart using example again used in the existing studies, and present result of performance accoriding to changing sample size and parameter.

• 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.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.