• Proceedings of the Korean Geotechical Society Conference
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• 2006.10a
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• pp.509-514
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• 2006

Considering the risk management, there are many examples and various studies for the corporation risk. However, I have never seen the project risk management that applied a construction site for practical approach. Therefore, I have developed a chart (I-Chart) for the project risk management, and also built a model (I-Chart scenario analysis) that I could use. I applied this model to container yard reclaimed land in harbor construction with approaching of geotechnical engineering.

• Journal of Korean Society for Quality Management
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• v.45 no.2
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• pp.209-225
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• 2017

Purpose: Since traditional p chart is unable to deal with the variation of attribute data, this paper proposes a new attribute control chart for nonconforming proportions incorporating overdispersion with a beta-binomial model. Methods: Statistical theories for control chart developed under the beta-binomial model and a new approach using this control chart are presented Results: False alarm probabilities of p chart with the beta-binomial model are evaluated and demerits of p chart under overdispersion are discussed from three examples. Hence a concrete procedure for the proposed control chart is provided and illustrated with examples Conclusion: The proposed chart is more useful than traditional p chart, individual chart to treat observed proportions nonconforming as variable data and Laney p' chart.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.315-324
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• 2010

We developed a design chart for very large floating structures through intensive hydroelastic analysis. Using this chart, one can predict the hydroelastic response of very large floating structures preliminarily at design stage without the cost-demanding hydroelastic analysis. This paper presents two new design charts based on the theory of VLFS. The purpose of the first design chart is to determine RAOs of the maximum longitudinal stress of VLFS considering properties of waves and structures. The design chart I can be applied to any sizes of VLFS in same aspect ratios and dimensionless stiffness parameters. The second design chart is developed to take into account the actual wave condition by using the Bretschneider spectrum with Beaufort sea state.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.973-976
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• 2004

So far, this report is written by knowledge and standard through several reference drawing and experienced contents with drawing hemming die. The contents about actual design is so huge that I will write about it next time. Timing chart is important to hemming die because of link position and numbers. Timing chart need a very much design time because link number and position have to applied for each case. In this paper developed an automatic timing chart and link position by relation and Pro/Program of Pro/Engineer. The method used relation rule of design parameter for timing chart. In the future, I believe that simple easy to correct and reasonable price hemming die will be producted.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.2
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• pp.255-262
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• 1992

A computer simulation methiod for costume design has been developed using LUMENA, a generic-purpose 2-dimensional graphic software. In this study the palette, tone chart, fabric chart, styling chart, and costume drawing were constructed on the computer. In costume design simulation, fabric swatches with various colors and patterns were applied to the base garment image taken by using a scanner or a video camera. In this procedure the original 3-dimensional effect was fully retained. Using this simulation method, a number of costume designs could be carried out in short time without actually making the garment. A portfolio including the tone chart, fabric chart, styling chart, costume drawing, and simulation results were made for the purpose of demonstration, using the animation tools of LUMENA.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.198-207
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• 1998

The p chart approximate to the normal distribution has a difficulty to analyze the process condition precisely when the negative LCL is occurred. Furthermore, the probability of Type I error increases compared with using its original binomial distribution. For a long time the p chart has been used as approximated to the normal distribution because of its easy use. However, it becomes rapid and convenient to calculate the binomial distribution through the development of computer and software, so it is strongly suggested to use the binomial distribution determining control limits to reduce the probability of Type I error. In this study, I suggest that the control limits can be designed in use of binomial distribution and they can be utilized without special software by illustrating the certain work for establishing p-chart with the commercial one(EXCEL).

• 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.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.485-495
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• 2018

The CCC-r chart is more effective than traditional attribute control charts for monitoring high-quality processes. In-control process parameters are typically unknown and should be estimated when implementing a CCC-r chart. Phase II control chart performance can deteriorate due to the effect of the estimation error. In this paper, we used the standard deviation of average run length (ARL) as well as the average of ARL to quantify the between-practitioner variability in the CCC-r chart performance. The results indicate that the CCC-r chart requires larger Phase I data than previously recommended in the literature in order to have consistent chart in-control performance among practitioners.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.37-45
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• 2016

Control chart is representative tools of statistical process control (SPC). It is a graph that plotting the characteristic values from the process. It has two steps (or Phase). First step is a procedure for finding a process parameters. It is called Phase I. This step is to find the process parameters by using data obtained from in-controlled process. It is a step that the standard value was not determined. Another step is monitoring process by already known process parameters from Phase I. It is called Phase II. These control chart is the process quality characteristic value for management, which is plotted dot whether the existence within the control limit or not. But, this is not given information about the economic loss that occurs when a product characteristic value does not match the target value. In order to meet the customer needs, company not only consider stability of the process variation but also produce the product that is meet the target value. Taguchi's quadratic loss function is include information about economic loss that occurred by the mismatch the target value. However, Taguchi's quadratic loss function is very simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. Also, it can be well explained by only on condition that the normal process. Spiring proposed an alternative loss function that called reflected normal loss function (RNLF). In this paper, we design a new control chart for overcome these disadvantage by using the Spiring's RNLF. And we demonstrate effectiveness of new control chart by comparing its average run length (ARL) with ${\bar{x}}-R$ control chart and expected loss control chart (ELCC).

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.172-180
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• 1991

The null hypothesis being tested by $the{\bar{X}}$ control chart is that the process is in control at a quality level ${\mu}o$. An ${\bar{X}}control$ chart is a tool for detecting process average changes due to assingnable causes. The major weakness of $the{\bar{X}}$ control chart is that it is relatively insensitive to small changes in the population mean. This paper presents one way to remedy this weakness is to allow each plotted value to depend not only on the most recent subgroup average but on some of the other subgroup averages as well. Two approaches for doing this are based on (1) moving averages and (2) exponentially weighted moving averages of forecasting method.