• Journal of Korean Society for Atmospheric Environment
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• v.20 no.E1
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• pp.1-14
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• 2004

Meteorological mechanisms in association with long-range transport of Asian dust in April 2001 have been investigated using weather maps, satellite images, TOMS and surface $PM_{10}$ data, backward trajectories, plus modeling output results (geopotential heights, horizontal wind vectors, potential temperatures, and streamlines). The results indicated that long -range transport of Asian dust to the west coast of North America was associated with strong westerlies between the Aleutian low and the Pacific high acting as a conveyor belt. Accelerating westerly flows due to cyclogenesis at the source regions over East Asia transported pollution from the continent to the central Pacific. When the system reached the Aleutian Islands, the intensity of troughs and the westerlies were amplified in the North Pacific. Thereafter the winds between the Aleutian Islands and the Pacific Ocean were more intensified from the air flow transport of the conveyor belt. Consequently, the strong wind in the conveyor belt enhanced the dust transport from the Pacific Ocean to the west coast of North America. This was evidenced by $PM_{10}$ concentration (maximum of about $100{\mu}g\;m^{-3}$) observed In California. Further evidence of the dust transport was found through the observation of satellite images, the distribution of TOMS aerosol index, and the analyses of streamlines and backward trajectories.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.1
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• pp.103-109
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• 2021

Fine chips generated by machining have an impact on machine failure and quality of machined products, it is necessary to remove the chips, so the microchip collection and removal device by rotating conveyor belt with neodymium permanent magnets was developed. In this research, to solve the problem for reducing the existing microchips in the tank, a micro-chip removal device by rotating conveyor belt with neodymium permanent magnets developed. In the development of micro-chip removal device, 3D CATIA modeling was used, and the flow analysis and the electromagnetic force analysis were performed with COMSOL Multiphysics program. To evaluate the performance of the prototypes produced, design of experiments (DOE) is used to obtain the effect of neodymium conveyor movement speed on chip removal for the ANOVA analysis of recovered powders. An experiment was conducted to investigate the effect of the conveyor feed rate on the chip removal performance in detail. As a result of the experiment, it was confirmed that the slower the feeding speed of the fine chip removing device, the more efficient the chip removal.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.109-116
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• 2023

This paper presents a network-based automation system for the detection of metallic objects in food and livestock. A metal detector is a core equipment used for the inspection required by HACCP. Since the existing metal detectors are manufactured as a single-body equipment, it is difficult to take into account various user requirements for the system. In order to overcome the drawback, this study presents a network-based automation system for metal detector utilizing an industrial fieldbus and modular components. The proposed system can effectively consider the various customer requirements and control schemes. The proposed system can also achieve the improvement in speed and success rate of detecting metallic objects. The effectiveness of the proposed system is demonstrated through a various experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2037-2042
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• 2017

The manufacturing facility is generally operated by a pre-set program under the existing factory automation system. On the other hand, the manufacturing facility must decide how to operate autonomously in Industry 4.0. Determining the operation mode of the production facility itself means, for example, that it detects the abnormality such as the deterioration of the facility at the shop-floor, prediction of the occurrence of the problem, detection of the defect of the product, In this paper, we propose a manufacturing process modeling using a queue for detection of manufacturing process abnormalities at the shop-floor, and detect abnormalities in the modeling using SVM, one of the machine learning techniques. The queue was used for M / D / 1 and the conveyor belt manufacturing system was modeled based on ${\mu}$, ${\lambda}$, and ${\rho}$. SVM was used to detect anomalous signs through changes in ${\rho}$.