• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.224-227
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• 2001

The preform design in metal forging plays a key role in improving product quality, such as ensuring defect-free property and proper metal flow. In industry, preforms are generally designed by the iterative trial-and-error approach, but this approach leads not only to significant tool cost but also to the down-time of the production equipment. It is thus necessary to reduce the time and the man-power through an effective method of perform design. In this paper, the equi-potential lines designed in the electric field are introduced to find the preform shape. The equi-potential lines obtained by the arrangement of the initial and final shapes are utilized for the design of the preform, and then applied for obtaining a fine preform in the foging process of the ball-joint socket.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.742-747
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• 2015

The quality of steel plate products is determined by the number of defects and the process problems are estimated by shapes of defects. Therefore pinholes defects of cold rolled steel have to be controlled. In order to improve productivity and quality of products, within each production process, the product is inspected by an adequate inspection system individually in the lines of steelworks. Among a number of inspection systems, we focus on the pinholes detection system. In this paper, we propose an embedded system using FPGA which can detect pinholes defects. The proposed system is smaller and more flexible than a traditional system based on expensive frame grabbers and PC. In order to detect consecutive defects, FPGAs acquire two dimensional image and process the image in real time by using correlation of lines. The proposed pinholes detection algorithm decreases arithmetic operations of image processing and also we designed the hardware to shorten the data path between logics due to decreasing propagation delay. The experimental results show that the proposed embedded system detects the reliable number of pinholes in real time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.9-17
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• 2010

Complex products may present more than one type of defects and these defects are not always of equal severity. These defects are classified according to their seriousness and effect on product quality and performance. So, demerit systems are very effective systems to monitor the different types of defects. Recently, Kang et al.(2009) proposed the revised Demerit-CUSUM for the evaluation of the Demerit-CUSUM control chart performance exactly. In this paper, we present an advanced Demerit control chart using the double EWMA technique. The double EWMA technique is very efficient and strong method for process control where defects and nonconformities occur with various defect types. Moreover, we compare exact performance of Demerit-CUSUM, Demerit-EWMA and Demerit-DEWMA control chart according to changing sample size or mean shifts magnitude. By the result, we confirm that the performance of Demerit-DEWMA control chart is more than the performance of the Demerit-CUSUM and Demerit-EWMA control chart.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.185-212
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• 2005

The ultimate objectives of the six sigma activities are to raise quality of products to the level where customers can be satisfied and to improve marketing efficiency through cost reduction. Recently, many businesses have been struggling to find out the most successful way to implement the six sigma to produce better results. This study is significant in a way that it provides readers with an actual evidence of efficiency and effectiveness of six sigma activities in marketing performance for the first time. The major data of this study can be divided into two categories ; First, secondary data research method was utilized to find out the effects of six sigma management on the quality and marketing performances, theoretically and empirically. Second, test of established hypotheses relevant to the effects of six sigma management on the quality and marketing performance based on the propositions drawn from existing literatures, and test hypotheses statistically. This study of six sigma looked into benefits in manufacturing industry in terms of improving quality, cutting cost and decreasing defection product-defect rate. In addition, the study has verified that how the quality performances can affect the marketing performances, such as enhancing corporate image, sales increase and customer satisfaction. The author believes that this study will help many businesses acquire best methods to increase sales and profits. And, business manager will be able to understand where to focus as they proceed with the six sigma project and improve corporate competitiveness.

• Journal of the Korea Safety Management & Science
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• v.20 no.3
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• pp.11-19
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• 2018

This study suggests a model of production information system that can reduce manufacturing lead time and uniformize quality by using DNC S/W as a part of constructing production information management system in the industrial field of the existing marine engine block manufacturing companies. Under the effect of development of this system, the NC machine interface device can be installed in the control computer to obtain the quality information of the workpiece in real time so that the time to inspect the process quality and verify the product defect information can be reduced by more than 70%. In addition, the reliability of quality information has been improved and the external credibility has been improved. It took 30 minutes for operator to obtain, analyze and manage the quality information when the existing USB memory is used, but the communication between the NC controller computer and the NC controller in real time was completed to analyze the workpiece within 10 seconds.

• Journal of the Korean Institute of Gas
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• v.19 no.2
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• pp.45-53
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• 2015

In order to improve the performance of the visual inspection process, in addition to existing automatic visual inspection machine and human inspectors have developed a new process configuration using a Naive Bayes classifier. By applying the classifier, defect leakage and human inspector's work amount could be improved at the same time. New classification method called AMPB was applied instead of conventional methods based on MAP classification. By experimental results using the filter product for camera modules, it was confirmed that it is possible to configure the process at the level of leakage ratio 1.14% and human inspector's work amount ratio 75.5%. It is significant that the result can be applied in such a wide range as gas leak detection which is the collaboration process between inspection machine and human inspector's

• The Plant Pathology Journal
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• v.27 no.1
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• pp.20-25
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• 2011

Gibberella zeae (anamorph: Fusarium graminearum), a homothallic (self-ferile) ascomycete with ubiquitous geographic distribution, causes serious diseases in several cereal crops. Ascospores (sexual spores) produced by this fungal pathogen have been suggested as the main source of primary inoculum in disease development. Here, we report the function of a gene designated GzRUM1, which is essential for ascospore formation in G. zeae. The deduced product of GzRUM1 showed significant similarities to the human retinoblastoma (tumor suppressor) binding protein 2 and a transcriptional repressor, Rum1 in the corn smut fungus (Ustilago maydis). The transcript of GzRUM1 was detected during the both vegetative and sexual stages, but was more highly accumulated during the latter stage. In addition, no GzRUM1 transcript was detected in a G. zeae strain lacking a mating-type gene (MAT1-2), a master regulator for sexual development in G. zeae. Targeted deletion of GzRUM1 caused no dramatic changes in several traits except ascospore formation. The ${\Delta}$GzRUM1 strain produced perithecia (sexual fruit bodies) but not asci nor ascospores within them. This specific defect leading to an arrest in ascospore development suggests that GzRUM1, as Rum1 in U. maydis, functions as a transcriptional regulator during sexual reproduction in G. zeae.

• Journal of Korea Foundry Society
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• v.39 no.1
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• pp.1-6
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• 2019

During the casting process, it is possible to minimize shrinkage and blowholes by modifying the casting design. However, it is impossible to eliminate these factors completely. Therefore, mechanical design engineers apply a sufficient safety factor owing to the possibility of insufficient performances of the cast products. In this paper, prediction method of the fatigue life of cast products containing shrinkage is conducted by using CT (computed tomography) and the SSM (shape simplification method), and additional fatigue analyses are carried out. The analysis results are then compared to results from actual experiments on samples with shrinkage defects. It is found to be that the considering actual shrinkage in cast products by means of stress and fatigue analyses is more accurate and effective. It is also considered that the proposed hot spot method provides us a good tool to predict the fatigue lifes of cast product.

• Journal of the Korea Safety Management & Science
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• v.23 no.3
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• pp.83-88
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• 2021

Recently, due to the aging of workers and the weakening of the labor base in the automobile industry, research on quality inspection methods through ICT(Information and Communication Technology) convergence is being actively conducted. A lot of research has already been done on the development of an automated system for quality inspection in the manufacturing process using image processing. However, there is a limit to detecting defects occurring in the automotive sunroof sealer application process, which is the subject of this study, only by image processing using a general camera. To solve this problem, this paper proposes a system construction method that collects image information using a infrared thermal imaging camera for the sunroof sealer application process and detects possible product defects based on the SVM(Support Vector Machine) algorithm. The proposed system construction method was actually tested and applied to auto parts makers equipped with the sunroof sealer application process, and as a result, the superiority, reliability, and field applicability of the proposed method were proven.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.208-216
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• 2020

With the spread of smart manufacturing, one of the key topics of the 4th industrial revolution, manufacturing systems are moving beyond automation to smartization using artificial intelligence. In particular, in the existing automatic machining, a number of machining defects and non-processing occur due to tool damage or severe wear, resulting in a decrease in productivity and an increase in quality defect rates. Therefore, it is important to measure and predict tool life. In this paper, ν-ASVR (ν-Asymmetric Support Vector Regression), which considers the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, was proposed and applied to the tool wear prediction problem. In the case of tool wear, if the predicted value of the tool wear amount is smaller than the actual value (under-estimation), product failure may occur due to tool damage or wear. Therefore, it can be said that ν-ASVR is suitable because it is necessary to overestimate. It is shown that even when adjusting the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, the ratio of the number of data belonging to ⲉ-tube can be adjusted with ν. Experiments are performed to compare the accuracy of various kernel functions such as linear, polynomial. RBF (radialbasis function), sigmoid, The best result isthe use of the RBF kernel in all cases