• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2001.11a
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• pp.42-42
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• 2001

The rate of coating consolidation influences the operation of several coating methods and the final quality of the coating layer. The rate of coating consolidation is characterized with a dynamic gloss meter at short times for a thin coating layer applied to the base sheet of interest. During the coating consolidation process, the laser gloss meter response curve exhibits two critical turning points that indicate the two coating immobilization points defined by the traditional methods. Five base sheets with several different coating suspensions are characterized. A model is proposed to estimate the rate of consolidation based on physical properties of the coating suspension, the base paper, and the liquid phase of the coating. The paper properties, especially the contact angle, are found to be an important factor in determining rate of consolidation. The model predicts the correct trends for the different coating suspensions and base sheets. The test method, along the model, can be used to determine the filtercake resistance of the coating layer for a thin and rapidly formed filtercake.

• Corrosion Science and Technology
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• v.23 no.3
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• pp.228-234
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• 2024

Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.

• Smart Structures and Systems
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• v.32 no.2
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• pp.123-133
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• 2023

This paper proposes a thermography-based coating thickness estimation method for steel structures using model-agnostic meta-learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured using an infrared (IR) camera. The measured heat responses are then analyzed using model-agnostic meta-learning to estimate the coating thickness, which is visualized throughout the inspection surface of the steel structure. Current coating thickness estimation methods rely on point measurement and their inspection area is limited to a single point, whereas the proposed method can inspect a larger area with higher accuracy. In contrast to previous ANN-based methods, which require a large amount of data for training and validation, the proposed method can estimate the coating thickness using only 10- pixel points for each material. In addition, the proposed model has broader applicability than previous methods, allowing it to be applied to various materials after meta-training. The performance of the proposed method was validated using laboratory-scale and field tests with different coating materials; the results demonstrated that the error of the proposed method was less than 5% when estimating coating thicknesses ranging from 40 to 500 ㎛.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.121.5-121
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• 2001

For the last decade, remarkable progress in the coating weight uniformity of hot dip galvanized product has been made to overcome the tightening quality constraints and produce cost-effective galvanized products. This progress results from research and development works for more efficient air knife, more accurate model of coating process, more precise measurement of coating weight and more efficient control logics. The activities for an efficient mathematical model to predict coating weight and several control logics which has been implemented on the No.1 CGL, No. 2 CGL, and PGL at KwangYang Steel Works are reviewed in this article.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.57-68
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• 1993

Air Wiping technique is widely used because of easy and efficient coating control in present CGL. Coaring weight is decided by nozzle header pressure, strip line speed and distance between strip and nozzle. Coating defects are results from unbalance of these factors and coating equipment calibration inaccuracy. Therefore, this study is mainly dealing with the cause of coating defects such as edge overcoating and coating deviation. The coptimum working condition is suggested by formulated coating model using collected working data. We developed two demension analysis program for air flow in nozzle and calculated dynamic pressure and air velocity with this program. The productivity and coating guality are improved by applying the result of this reserach.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.2
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• pp.192-199
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• 2002

In continuous galvanizing process, the mass of zinc deposited and its distribution are controlled by the air pressure, effective distance from the air knife nozzle to the steel strip surface and line speed. Coating defects are resulted from the unbalance of these control factors and the inaccuracy of coating equipments. This paper investigates the main cause of coating deviation and a new air knife system for control of coating thickness was developed. We investigate dynamic pressure variation by air knife types. It is found that the coating deviation is caused by the unbalance of dynamic pressure, the irregularity of strip position, and the strip vibration. Formulating a useful coating model by using present working condition, an optimal working condition is suggested. The productivity and coating quality are improved by applying the result of this research at the shop floor.

• Journal of the Semiconductor & Display Technology
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• v.17 no.4
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• pp.80-85
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• 2018

The present investigation on optical fiber mass manufacturing features the computational modeling and simulation on a double layer liquid coating process on glass fiber surface. The computational model employs a simplified geometry of typical fiber coating system which consists of primary and secondary coating dies along with secondary coating cup. The viscous dissipation in coating flow is incorporated into the double layer coating process simulations. Heavy temperature dependence of coating liquid viscosity is also considered in the model. The computational results found that the effects of viscous dissipation on both primary and secondary coating layer thicknesses are highly significant at higher drawing speed. Several important coating process parameters such as supply temperature and pressure of primary and secondary coating liquids are investigated and discussed in order to appreciate how those parameters affect the double layer coating layer thickness on fast moving glass fiber.

• Advances in biomechanics and applications
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• v.1 no.1
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• pp.23-40
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• 2014

This paper examines the blood chamber of a left ventricular assist device (LVAD) under static loading conditions and standard operating temperatures. The LVAD's walls are made of a temperature-sensitive polymer (ChronoFlex C 55D) and are covered with a titanium nitride (TiN) nano-coating (deposited by laser ablation) to improve their haemocompatibility. A loss of cohesion may be observed near the coating-substrate boundary. Therefore, a micro-scale stress-strain analysis of the multilayered blood chamber was conducted with FE (finite element) code. The multi-scale model included a macro-model of the LVAD's blood chamber and a micro-model of the TiN coating. The theories of non-linear elasticity and elasto-plasticity were applied. The formulated problems were solved with a finite element method. The micro-scale problem was solved for a representative volume element (RVE). This micro-model accounted for the residual stress, a material model of the TiN coating, the stress results under loading pressures, the thickness of the TiN coating and the wave parameters of the TiN surface. The numerical results (displacements and strains) were experimentally validated using digital image correlation (DIC) during static blood pressure deformations. The maximum strain and stress were determined at static pressure steps in a macro-scale FE simulation. The strain and stress were also computed at the same loading conditions in a micro-scale FE simulation.

• Journal of the Semiconductor & Display Technology
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• v.3 no.3
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• pp.41-44
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• 2004

The aim of this study is the confirmation of the coating uniformity affected by the surface tension and wall attachment angle in a slit-coater model. In this work, we use the commercial code (Fluent) to solve the two-phase flow formed with air and photo resist numerically. The results show that the surface tension is the most important factor to determine the coating efficiency in the view of coating uniformity, and the coating uniformity is 2% for our slit-coater model and conditions. To improve the coating uniformity, it is in need of minimization of the sidewall effect of slit-coater.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.226-231
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• 2019

A WTCI is an important criteria for evaluating an mount of patient's tongue coating in tongue diagnosis. However, Previous WTCI tongue coating evaluation methods is a most of quantitatively measuring ration of the extracted tongue coating region and tongue body region, which has a non-objective measurement problem occurring by exposure conditions of tongue image or the recognition performance of tongue coating. Therefore, a WTCI based on deep learning is proposed for classifying an amount of tonger coating in this paper. This is applying the AI deep learning method using big data. to WTCI for evaluating an amount of tonger coating. In order to verify the effectiveness performance of the deep learning in tongue coating evaluating method, we classify the 3 types class(no coating, some coating, intense coating) of an amount of tongue coating by using CNN model. As a results by testing a building the tongue coating sample images for learning and verification of CNN model, proposed method is showed 96.7% with respect to the accuracy of classifying an amount of tongue coating.