• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.65-70
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• 2001

This Paper Propose the control chart Pattern to provide a more comprehensive scheme for detecting process shifts using individual observations in start-up process. In this paper, which uses the backpropagation algorithm two samples are fed into the trained neural network to provide outputs ranging from 0 to 1. The main advantage of using neural networks approach with a control chart is that the neural network has almost no delay in detecting small shift. This paper illustrates how neural networks can provide a useful method for optimizing parameter(connection weights) that affect process control. Simulation results show that the performance of the proposed control chart using the neural network (NNCC) is quite promising.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.83-95
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• 2018

With recent technological advances in the shipbuilding industry, vessels have been improved in size and performance. As a result, an accident such as grounding, caused by a single ship-to-ship collision, could lead to a large-scale maritime disaster. Considering the seriousness of the situation, the international community has been consistently updating the standards for Electronic Navigational Chart(ENC) to improve the maritime safety. S-57, the existing ENC standard governed by the International Hydrographic Organization(IHO), includes standards for generating conventional binary-type ENC data sets. The S-57 standard, however, has not been updated since the release of Version 3.1 in December 2000. Since then, the standard has failed to reflect technological development regarding maritime spacial information, which has been consistently improving. In an effort to address this concern, the IHO designated S-100, i.e., the next-generation ENC production standard. S-100 differs from S-57 in data exchange type. Contrary to the conventional ENC standards, which use binary-type data, S-10X, based on the next-generation ENC standards, uses ENC data composed of Feature Catalogue, Portrayal Catalogue, and GML. Considering this fact, it is necessary to update S-58, the ENC validation check standard, or designate a new standard for ENC validation checks. This study is developed own software to implement validation checks for new types of data, and identified improvement points based on the test results.

• Journal of the Korean Wood Science and Technology
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• v.8 no.1
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• pp.22-27
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• 1980

Quantitative assessment of edge blunting of saw-teeth was carried out by TALYSURF. 1. Using the following equation, the real shape of a saw-tooth can be traced on the graph of TALYSURF. ${\frac{{\Delta}h}{h}}={\frac{V{\Delta}_x}{V_x}}$ {${\Delta}h$: vertical distance of stylus h: vertical distance in chart $V{\Delta}_x$: Velocity of stylus $V_x$: velocity of chart} 2. As shown on Fig 2, the error from stylus itself can be calculated by following equation. i) 13.8${\mu}{\leqq}$x<20.4${\mu}$ y=-0.2246x+4.59${\mu}$ ii) 0${\leqq}$x<13.8${\mu}$ y=${\sqrt{(-18{\mu})^2-x^2}}-1.42x+32.7{\mu}}$ 3. The relationship between profile of saw-tooth and error from stylus itself can be calculated by following equation. $E(%)=\frac{f(r){\times}{\frac{4}{18{\mu}}}}{f(R){\times}{\frac{R}{18.5{\mu}}}-f(r){\times}{\frac{r}{18{\mu}}}}{\times}100$ {E(%)${\frac{error\;of\;stylus}{dullness\;of\;saw\;tooth}}{\times}100$ r: radius of stylus tip R: radius of tip which is drawn in graph of talysurf f(r) : error of stylus f(R) : dullness of tip which is drawn in graph of talysurf} 4. The graph of maximum error and profile of saw-tooth was parabola.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.981-999
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• 2017

In the standard control chart assuming a simple random model, we estimate the process variance without considering the between-sample variance. If the between-sample exists in the process, the process variance is under-estimated. When the process variance is under-estimated, the narrower control limits result in the excessive false alarm rate although the sensitivity of the control chart is improved. In this paper, using the variance component model to incorporate the between-sample variance, we set the control limits using both the within- and between-sample variances, and evaluate the efficiency of the control chart in terms of the average run length (ARL). Considering the most widely used control chart types such as ${\bar{X}}$, EWMA and CUSUM control charts, we compared the differences between two cases, Case I and Case II, where the between-sample variance is ignored and considered, respectively. We also considered the two cases when the process parameters are given and estimated. The results showed that the false alarm rate of Case I increased sharply as the between-sample variance increases, while that of Case II remains the same regardless of the size of the between-sample variance, as expected.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.487-501
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• 2017

A machine vision system (MVS) is a computer system that utilizes one or more image-capturing devices to provide image data for analysis and interpretation. Recently there have been a number of industrial- and medical-device applications where control charts have been proposed for use with image data. The use of image-based control charting is somewhat different from traditional control charting applications, and these differences can be attributed to several factors, such as the type of data monitored and how the control charts are applied. In this paper, we investigate the adjustment effect of image size and region of interest (ROI) size, when we use control charts to monitor grayscale image data in industry.

• 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 Korean Tunnelling and Underground Space Association
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• v.17 no.4
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• pp.441-455
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• 2015

In the present study, a face safety monitoring system was developed that will enable judging collapse risks on faces during tunnel construction to secure workers' safety. This system enables detecting abnormal behaviors of faces by analyzing the displacement of faces measured in real time using the x-MR control chart technique. In addition, an algorithm to judge false alarms was developed so that abnormal behaviors of faces and errors occurring in the process of work can be distinguished from each other by comparing the number of measured values exceeding the management criteria and moving range k. The results of the present study are applicable to real-time monitoring of behavior on the face in dangerous ground sections to minimize damage to workers.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.187-196
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• 2016

We conducted three-dimensional finite element analysis to predict the presence of upcoming fault zones during tunneling. The analysis considered longitudinal displacements measured at tunnel face, and used 28 numerical models with various fault attitudes. The x-MR (moving range) control chart was used to analyze quantitatively the effects of faults distributed ahead of the tunnel face, given the occurrence of a longitudinal displacement. The numerical models with fault were classified as fault gouge, fault breccia, and fault damage zones. The width of fault cores was set to 1 m (fault gouge 0.5 m and fault breccia 0.5 m) and the width of fault damage zones was set to 2 m. The results, suggest that fault centers could be predicted at 2~26 m ahead of the tunnel face and that faults could be predicted earliest in the 45° dip model. In addition, faults could be predicted earliest when the angle between the direction of tunnel advance and the strike of the fault was smallest.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.69-79
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• 1997

We investigate both of central and dispersion tendencies of the observed test statistics in control charts in order to judge whether a production process is abnormal or not. In order to do it, first, we study about detection of changes of the population mean as a central tendency The $\bar{x}$ and x control charts are used for detecting the change of the population mean $\mu$. We shows the probability detecting the change of population mean using the $\bar{x}$ and x control charts. Secondly, we study about detection of changes of the population standard deviation as a dispersion tendency in the s control chart. In our studies, for the given several parameters the detection probabilities of changes of central and dispersion tendencies are calculated, the necessary sample size values n are suggested for detecting the changes, and their informations are given as various tables.

• The Journal of Korean Medicine
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• v.24 no.3
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• pp.118-129
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• 2003

Objective : To learn the distributional characteristics of Sasang constitutions, Methods : We statistically analyzed those 1338 patients who had been treated at Iksan Wonkwang Oriental Medicine during the period of three years from 2000 to 2002. The data were obtained through the electronic chart developed by Kim Jong- Yeol, and analyzed using the statistical Package SPSS. Results : The distributional ratio of Soeumin : Soyangin : Taeumin was 22.8 : 29.2 : 47.8. Thus the hypothesis : 'the distributional ratio of Soeumin : Soyangin : Taeumin is 2 : 3 : 5' was barely rejected by $x^2$ test for goodness-of-fit at the significance level of 5 %. When $x^2$ test for homogeneity was applied, the distributional characteristics between women and men were different and the distributional characteristics among several age groups were different under significance level of 5%. Conclusion : Though the hypothesis: 'the distributional ratio of Soeumin : Soyangin : Taeumin is 2 : 3 : 5' was rejected by $x^2$ test at the significance level of 5%, the observed distributional ratio was not so far away from the hypothesis.