• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2002.11a
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• pp.14-19
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• 2002

In this study, as Cu diffusion barrier, tantalum nitrides were successfully deposited on Si(100) substrate and SiO2 by plasma assisted atomic layer deposition(PAALD) and thermal ALD, using pentakis (ethylmethlyamino) tantalum (PEMAT) and $NH_3$ as precursors. The TaN films were deposited on $250^{\circ}$C by both method. The growth rates of TaN films were $0.8{\AA}$/cycle for PAALD and $0.75{\AA}$/cycle for thermal ALD. TaN films by PAALD showed good surface morphology and excellent step coverage for the trench with an aspect ratio of h/w - $1.8 : 0.12 \mu\textrm{m}$ but TaN films by thermal ALD showed bad step coverage for the same trench. The density for PAALD TaN was $11g/\textrm{cm}^3$ and one for thermal ALD TaN was $8.3g/\textrm{cm}^3$. TaN films had 3 atomic % carbon impurity and 4 atomic % oxygen impurity for PAALD and 12 atomic % carbon impurity and 9 atomic % oxygen impurity for thermal ALD. The barrier failure for Cu(200nm)/TaN(l0nm)/$SiO_2(85nm)$/Si structure was shown at temperature above $700^{\circ}$C by XRD, Cu etch pit analysis.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.4
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• pp.177-184
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• 2005

This paper proposes a improved investment priority decision method of the facilities considering the reliability of distribution networks. The proposed method decides a investment order of the facilities combining, by fuzzy rules, the investment priority decision of KEPCO and the priority decision considering reliability evaluation indices. Where reliability evaluation indices are SAIFI(System Average Interruption Frequency Index) and SAIDI(System Average Interruption Duration Index), as referred to evaluation index for sustained interruption. The reliability analysis method of distribution networks applied in this paper utilizes analytic method, where the used reliability data is historical data of KEPCO. Particularly, we assumed that the failure rate increased as the equipment ages. To verify the performance of the proposed method, we applied it with the planned projects to reinforce the weak facility electrical facilities in KEPCO in 2004. The evaluation result showed that, under a limited budget, the reliability of the KEPCO in the Busan region using the proposed method can be enhanced than using the conventional KEPCO's method. Therefore, the results verify the proposed method can be efficiently used in the actual priorities method for investing the electrical facilities.

• KIEE International Transactions on Power Engineering
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• v.5A no.3
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• pp.260-268
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• 2005

This paper proposes an improved investment pnonty decision method of facilities considering the reliability of distribution networks. The proposed method decides an investment order of the facilities combining, by fuzzy rules, the investment priority decision by KEPCO and that by reliability evaluation indices. The reliability evaluation indices are SAIFI (System Average Interruption Frequency Index) and SAIDI (System Average Interruption Duration Index). The reliability analysis method of distribution networks applied in this paper utilizes the analytic method, where the used reliability data is the historical data of KEPCO. Particularly, we assumed that the failure rate increases as the equipment ages. To verify the performance of the proposed method, we applied it with the planned projects to reinforce the weak electrical facilities in KEPCO in 2004. The evaluation result showed that, under a limited budget, the reliability of KEPCO in the Busan region using the proposed method could be enhanced if used rather than the conventional method typically in place. Therefore, the results verify that the proposed method can be efficiently used in the actual priorities method for investing in the electrical facilities.

• Transactions on Electrical and Electronic Materials
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• v.18 no.4
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• pp.190-194
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• 2017

Present-day solar panels incorporate inverters as their core components. Switching devices driven by specialized power controllers are operated in a transformerless inverter topology. However, some challenges associated with this configuration include the absence of isolation, causing leakage currents to flow through various components toward ground. This inevitably causes power losses, often being also the primary reason for the power inverters' analog equipment failure. In this paper, various aspects of the leakage currents are studied using different circuit analysis methods. The primary objective is to convert the leakage current energy into a usable DC voltage source. The research is focused on harvesting the leakage currents for producing circa 1.1 V, derived from recently developed rectifier circuits, and driving a $200{\Omega}$ load with a power in the milliwatt range. Even though the output voltage level is low, the harvested power could be used for charging small batteries or capacitors, even driving light loads.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.61-68
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• 2004

Recently, there has been an increasing demand for computer-vision based inspection and/or measurement system as a part of factory automation equipment. Existing manual inspection method can inspect only specific samples and has low measuring accuracy as well as it increases working time. Thus, in order to improve the objectivity and reproducibility, computer-aided analysis method is needed. In this paper, front and side profile inspection and/or data transfer system are developed using computer-vision during the inspection process on three kinds of pipes coming from a forming line. Straight line and circle are extracted from profiles obtained from vision using Laplace operator. To reduce inspection time, Hough Transform is used with clustering method for straight line detection and the center points and diameters of inner and outer circle are found to determine eccentricity and whether good or bad. Also, an inspection system has been built that each pipe's data and images of good/bad test are stored as files and transferred to the server so that the center can manage them.

• Journal of Drive and Control
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• v.14 no.4
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• pp.71-78
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• 2017

The power train of hydro-mechanical continuously variable transmission (HMCVT) for 8-ton class forklift includes hydro-static units, hydraulic multi-wet disc brake & clutches and complex helical & planetary gears. The helical & planetary gears are key components of HMCVT's power train wherein strength problems are the main concerns including gear bending stress, gear compressive stress, and scoring failure. Many failures in power train gears of HMCVT are due to the insufficient gear strength and resonance problems caused by major excitation forces, such as gear transmission error of mating gear fair in the transmission. In this study, wherein excitation frequencies are the gear tooth passing frequencies of the mating gears, a Campbell diagram is used to calculate the power train gears' critical speeds. Mode shapes and natural frequencies of the power train gears are calculated by CATIA V5. These are used to predict resonance failures by comparing the actual working speed range with the critical speeds due to the gear transmission errors of HMCVT's power train gears.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.75-86
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• 2019

Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

• Journal of Aerospace System Engineering
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• v.12 no.1
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• pp.57-67
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• 2018

The APD (Antenna Pointing Driver) is an electronic equipment tool that is used to drive the two-axis gimbal-type antenna for the image data transmission of CAS (Compact Advanced Satellite). In this study, a heat dissipation of EEE (Electrical, Electronic and Electromechanical) is reviewed, to identify the parts that directly affected its efficiency, lifetime as well as the reliability of the structure. This event eventually incurs a failure of the EEE part itself, or even the entire satellite system as noted in experiments in this case. To guarantee reliability of electronic equipment during the mission, the junction temperature of EEE parts is considered a significant and important design factor, and subsequently must be secured within the allowable range. Therefore, the notation of the thermal analysis considering the derating is indispensable, and a proper thermal mathematical model should be constructed for this case. In this study, the thermal design and thermal analysis are performed to confirm the temperature requirement of the APD. In addition, we noted that the validity of the thermal model, according to each of the identified modeling methods, was therefore compared through the thermal analysis utilized in this case.

• Composites Research
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• v.32 no.5
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• pp.279-283
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• 2019

A flight training simulator of a fully spherical configuration is being developed to precisely and quickly control six degrees of freedom (Dof) motions especially with unlimited rotations. The full-scale simulator should be designed with a lightweight material to reduce inertial effects for fast and stable feedback controls while no structural failure is ensured during operations. In this study, a sandwich composite consisting of glass fiber reinforced plastics and a foam core is used to obtain high specific strengths and specific stiffnesses. T-type stainless steel frames are inserted to minimize the deformation of the sphere curvature. Finite element analysis is carried out to evaluate structural safety of the simulator composed of the sandwich sphere and steel frames. The analysis considers the weights of the equipment and trainee and it is assumed to be 200 kg. Gravity acceleration is also considered. The stresses and displacement acting on the simulator are calculated and the safety is assessed under two different situations.

• Journal of the Korean Institute of Gas
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• v.28 no.2
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• pp.93-104
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• 2024

Facility diagnosis is essential for the smooth operation and life extension of rotating equipment used in industrial sites. Compared to other diagnostic methods, vibration diagnosis can find most of the initial defects, such as unbalance, alignment failure, bearing defects and resonance, compared to other diagnostic methods. Therefore, vibration analysis is the most commonly used facility diagnosis method in industrial sites, and is usefully used as a predictive preservation (PdM) technology to manage the condition of the facility. However, since the vibration diagnosis method is performed based on experience based on the standard, it is carried out by experts. Therefore, it is intended to contribute to the reliability of the facility by establishing a system that anyone can easily judge defects by establishing a vibration diagnosis method performed based on experience as a knowledgeable code system. An algorithm was developed based on the ISO-20816 standard for vibration measurement, and the reliability was verified by comparing the results of vibration measurement at various demonstration sites such as petrochemical plant compressors, hydrogen charging stations, and industrial machinery with the results of analysis using a development system. The developed algorithm can contribute to predictive maintenance (PdM) technology that anyone can diagnose the condition of the rotating machine at industrial sites and identify defects early to replace parts at the exact time of replacement. Furthermore, it is expected that it will contribute to reducing maintenance costs and downtime due to the failure of rotating machines when applied to various industrial sites such as oil refining facilities, transportation, production facilities, and aviation facilities.