• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.187-194
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• 2020

In today's process-oriented industries, such as semiconductor and petrochemical processes, autocorrelation exists between observed data. As a management method for the process where autocorrelation exists, a method of using the observations is to construct a batch so that the batch mean approaches to independence, or to apply the EWMA (Exponentially Weighted Moving Average) statistic of the observed value to the EWMA control chart. In this paper, we propose a method to determine the batch size of UBM (Unweighted Batch Mean), which is commonly used as a management method for observations, and a method to determine the optimal batch size based on ARL (Average Run Length) We propose a method to estimate the standard deviation of the process. We propose an improved control chart for processes in which autocorrelation exists.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.101-106
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• 2014

New control charts under repetitive sampling are proposed, which can be used for variables and attributes quality characteristics. The proposed control charts have inner and outer control limits so that repetitive sampling may be needed if the plotted statistic falls between the two limits. Particularly, the new np and variable X-bar control charts under repetitive sampling are considered in detail. The in-control and out-of-control average run lengths are analyzed according to various process shifts. The performance of the proposed control charts is compared with the existing np and the X-bar control charts in terms of the average run lengths.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.313-321
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• 2010

The coefficient of variation represents the ratio of the standard deviation to the mean, and it is a useful statistic for comparing the degree of variation from one data series to another, even if the means are drastically different from each other. Recently, the CV control chart is developed for monitoring processes in such situations. However, the CV control chart has low performance in detecting small shift. Due to the development of equipment and technique, currently, small shift of process occurs more frequently than large shift. In this paper, we proposes the CV-CUSUM control chart using CUSUM scheme which is cumulative sum of the deviations between each data point and a target value to detect a small shift in the process. We also found that the FIR(fast initial response) CUSUM control chart is especially valuable at start-up or after a CV-CUSUM control chart has signaled out-of-control.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.14-20
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• 2004

The coefficient of variation(CV) which is a relatively dimensionless measure of variability is widely used to describe the variation of sample data. However, the properties of CV distribution are little available and few research has been done on estimation and interpretation of CV. In this paper, we give an outline of statistical properties of coefficient of variation and design of control chart based on this statistic. Construction procedures of control chart are presented. The proposed control chart is an efficient method to monitor a process variation for short production run situation. Futhermore, we evaluated the performance of CV control chart by average run length(ARL).

• Journal of Integrative Natural Science
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• v.5 no.4
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• pp.246-252
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• 2012

Multivariate cumulative sum (CUSUM) control charts for simultaneously monitoring both means and variances under multivariate normal process are investigated. Performances of multivariate CUSUM schemes are evaluated for matched fixed sampling interval (FSI) and variable sampling interval (VSI) features in terms of average time to signal (ATS), average number of samples to signal (ANSS). Multivariate Shewhart charts are also considered to compare the properties of multivariate CUSUM charts. Numerical results show that presented CUSUM charts are more efficient than the corresponding Shewhart chart for small or moderate shifts and VSI feature with two sampling intervals is more efficient than FSI feature. When small changes in the production process have occurred, CUSUM chart with small reference values will be recommended in terms of the time to signal.

• Proceedings of the Korean Reliability Society Conference
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• 2000.04a
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• pp.123-129
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• 2000

SPC is the quality improvement technique of gathering since Motorola of U.S.A. have used SPC technique as a statistical process control method for promoting 6-sigma quality improvement strategy in 1988. In Korea, small and medium-sized enterprises are needed building of a system for statistical production control . In the present study, the methods of building SPC system with a moderate cost using a graphic programs of easy-to-use and high flexibility for small and medium-sized enterprises were inquired. The SPC system which enables statistic marking (maximum, minimum, mean, standard deviation, process capability index) and graph marking (X-Y coordinates and histogram) using LabVIEW 5.0, the graphic program by National Instrument Co., Ltd. was implemented in this study.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.617-626
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• 2012

Multivariate Shewhart control charts are considered for the simultaneous monitoring the variance-covariance matrix when the joint distribution of process variables is multivariate normal. The performances of the multivariate Shewhart control charts based on control statistic proposed by Hotelling (1947) are evaluated in term of average run length (ARL) for 2 or 4 correlated variables, 2 or 4 samples at each sampling point. The performance is investigated in three cases, that is, the variances, covariances, and variances and covariances are changed respectively.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.117-122
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• 2005

Variable sampling rate(VSR) scheme varies the sampling rate for the current sample depending on the previous value of the control statistic. In this paper, we propose EWMA control charts with variable parameter(VP) scheme, which allows both the sample rate(the sample size or the sampling interval) and the weight to vary. We investigate the effectiveness of the VP scheme relative to the fixed parameter(FP) scheme and the VSR scheme in EWMA control charts. It is shown that using the VP scheme gives some improvements to the ability in detecting small and moderate shifts in the process normal mean.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.576-585
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• 2021

This study was a descriptive research study to examine the factors influencing cyberbullying tendency among college students. The data used in this study were collected from July 31 to August 13, 2020, from 396 students attending universities across South Korea. The collected data were analyzed using frequency, percentage, mean, standard deviation, Pearson correlation coefficients, PROCESS macro model 4, Bootstrap, Sobel test using IBM SPSS Statistics version 20.0 and PROCESS macro for SPSS. The results of this study are as follows. First, there was a significantly negative correlation between academic stress and self-control (r=-.246, p<.001). There was also a positive correlation between academic stress and cyberbullying tendency, but it was not significant (r=.096, p=.055). Second, the mediation effect of self-control is significant between academic stress and cyberbullying tendency (R2=.039, p<.001). Therefore, Academic stress and self-control should be considered in the development of cyberbullying prevention programs, and further research is also needed to verify the effectiveness of the cyberbullying prevention program based on this study.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.657-676
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• 2011

Properties of statistical process control procedures may not be derived analytically in many cases; however, the application of a Markov chain can solve such problems. This article shows how to derive the properties of the process control procedures using the generated Markov chains when the control statistic satisfies the Markov property. Markov chain approaches that appear in the literature (such as the statistical design and economic design of the control chart as well as the variable sampling rate design) are reviewed along with the introduction of research results for application to a new control procedure and reset chart. The joint application of a Markov chain approach and analytical solutions (when available) can guarantee the correct derivation of the properties. A Markov chain approach is recommended over simulation studies due to its precise derivation of properties and short calculation times.