• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.435-436
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• 2012

• Journal of the Korea Safety Management & Science
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• v.23 no.3
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• pp.27-33
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• 2021

The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

• The Pure and Applied Mathematics
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• v.24 no.4
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• pp.211-226
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• 2017

In this paper, machine learning models employed in various fields are discussed and applied to KOSPI200 stock index return forecasting. The results of hyperparameter analysis of the machine learning models are also reported and practical methods for each model are presented. As a result of the analysis, Support Vector Machine and Artificial Neural Network showed a better performance than k-Nearest Neighbor and Random Forest.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.349-355
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• 2013

Recently, there is an increasing need to produce more precise products with small deviations from defined target values. Machine capability is the ability of a machine tool to produce parts within a tolerance interval. Capability indices are a statistical way of describing how well a product is machined compared to defined target values and tolerances. Today, there is no standardized way to acquire a machine capability value. This paper describes a method for evaluating machine capability indices in machining centers. After the machining of specimens, the straightness, roundness, and positioning accuracy were measured by using CMM (coordinate measuring machine). These measured values and defined tolerances were used to evaluate the machine capability indices. It will be useful for the industry to have standardized ways to choose and calculate machine capability indices.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.3
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• pp.7-12
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• 2011

In the recent field of 5-axis machine tools, it is necessary to improve machining ability. The tilting index table is a key unit in order to manufacture some non-rotational and 3-dimensional parts by using conventional machining centers. In this study, the structural analysis of a tilting index table is carried out and the displacement and distribution of stress in the tilting index table is analysed to design the table safely. The modal analysis is performed in order to confirm the frequency response about the vibration having a large effect on the machine tools. The dynamic analysis is performed in order to confirm the rigidity, and the structural stability has been verified.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.210-216
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• 1997

A study to select ground colors of Fuji apple for maturity index which are needed to standardize grading of the apples is presented. Two extreme colors of immature and fully mature Fuji and Zonagold apples produced in Korea were determined. Various ground colors of Fuji apple between the two extreme colors were collected and classified by human vision and colors of Fuji apple for maturity index were selected from the classification. Coordinates of the selected colors in xy chromaticity diagram were determined by spectrophotometers to define them in a standard coordinate system. Coordinates of the colors in r-g chromaticity diagram using a color machine vision system were also determined to use the colors in apple grading by the machine vision system. Grading Fuji apples using the machine vision system was performed and result of the grading was compared with Ending results of human vision and colorimeter. The comparison was performed with the same Fuji apple samples and showed 65% md 75% of same grades, respectively, as the grades determined by the machine vision system. Differences of fading performance between the compared three grading methods were explained as mainly because of the differences of observation area of the grading methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.115-116
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• 2010

• Journal of the Korean Society for Precision Engineering
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• v.28 no.8
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• pp.894-903
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• 2011

In this paper, the capability index is introduced in order to improve the reliability of new concept machine tools and the method to improve the machine accuracy from the analysis of cutting process, statistical methodology and influence factors are proposed. In addition, the rib structure of bed and column in machine tools is analyzed by using the thermal impact method in order to analogize the rib pattern which has the small thermal deformation under thermal boundary condition. In the analysis of column rib structure, thermal boundary condition is separated to heat conduction and heat transfer to appropriate real boundary condition. Finally, performance chart of bed and column rib structure is provided for designer to estimate each rib pattern and select rib structure appropriating to thermal condition.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.60-65
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• 2022

This study focuses on the driving control design of an index, which is a key component of a rotary transfer machine that is effective in improving productivity and reducing manufacturing costs by shortening cycle time. Although various index studies have been conducted on the rotation of workpieces such as general-purpose machine tools and tilting indices, the development of an index for rotary transfer machines for transfer is insufficient. The index consists of a body, table, hydraulic cylinder, motor, reducer, and curved coupling. The torque of the table for driving was selected, and the angular velocity and torque pattern were simulated using the motor manufacturer's program. The specifications of the drive motor were determined based on the selected torque.