• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.170-174
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• 2004

Despite the widespread use in the various manufacturing industries, the full automation of the robotic CO$_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an Radial basis function network model to predict the weld top-bead width as a function of key process parameters in the robotic CO$_2$ welding. and to compare the developed model and a simple neural network model using two different training algorithms in order to verify performance. of the developed model.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.66-70
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• 2005

The full automation of welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an neural network model to predict the weld top-bead height as a function of key process parameters in the welding. and to compare the developed model and a simple neural network model using two different training algorithms in order to select an optimal neural network model.

• Journal of Ocean Engineering and Technology
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• v.11 no.1
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• pp.36-43
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• 1997

Weld bead shape is an important measure for evaluation of weld quality. Many welding parameters have influence on the weld bead shape. The quantitative relationship between welding parameters and bead shape, however, is not determined yet because of their high complexity and many unknown factors. Fuzzy expert system is an advanced expert system which uses fuzzy rules and approximate reasoning. It is a vert useful tool for welding technology because is can process rationally the uncertain and inexact information such as the welding information. In this paper, the empirical and the qualitative relationship between welding parameters and bead shape are analyzed and represented by fuzzy rules. They are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. Weld bead shape is estimated from the welding parameters using fuzzy expert system. The result of comparison between measured values of weld bead by welding experiments and the estimates values by fuzzy expert system shows a good consistancy.

• Journal of the Korean Society for Heat Treatment
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• v.18 no.2
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• pp.105-111
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• 2005

In sheet metal forming, drawbeads are often used to control uneven material flow, which may cause defects such as wrinkles, fractures, surface distortion and springback. Appropriate setting and adjusting of the drawbead force is one of the most important parameters in sheet forming process control. Therefore in this study, drawbead test was performed at various bead surface treatment conditions to clarify the frictional characteristics between sheet and drawbead. Furthermore, the differences in drawing force between circular and rectangular shape beads have also been measured to estimate the effectiveness of bead shape on the material flow control. The results show that drawing and friction characteristic were strongly influenced by surface treatments of bead and bead shapes.

• Journal of the Korea Organic Resources Recycling Association
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• v.17 no.4
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• pp.74-80
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• 2009

Effect of dye wastewater on heavy metal removal using carboxylated alginic acid bead was performed. When carboxylated alginic acid bead was used as support, effect of dye wastewater on adsorption of $Pb^{2+}$ and $Cu^{2+}$ ions was very small. Also, when $Pb^{2+}$ was coexisted with dye wastewater, adsorption process was almost completed within 2-3 hrs and $Pb^{2+}$ ions (50 ppm) was almost removed with 0.3g of bead. This result means that carboxylated alginic acid bead has effective adsorbent for heavy metal removal in dye wastewater.

• Journal of Marine Bioscience and Biotechnology
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• v.12 no.2
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• pp.81-90
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• 2020

Sialic acid, which is contained in about 60-160 mg/kg in the edible bird's nest (EBN), is known to facilitate in the proper formation of synapses and improve memory function. The objective of this study is to extract effectively the sialic acid from edible bird's nest using affinity bead technology (ABT). After preparing the non-polar polymeric bead "KJM-278-28A" having a porous network structure, and then desorbed sialic acid was concentrated and dried. The analysis of the physicochemical properties of bead "KJM-278-28A" showed that the particle size was 400-700 ㎛, the moisture holding capacity was 67-70%, the surface area (BET) was 705-900 ㎡/g, and the average pore diameter 70-87 Å. The adsorption capacity of the bead "KJM-278-28A" for sialic acid was shown a strong physical force to bind sialic acid to the bead surface of 400 mg/L. In addition, as a result of analyzing the adsorption and desorption effects of sialic acid on water, ethanol, and 10% ethanol on the bead, it was confirmed that desorption effectively occurs from the beads when only ethanol is used. As a result of HPLC measurement of the separated sialic acid solution, a total of four sialic acid peaks of N-acetyl-neuraminic acid (Neu5Ac), α,β-anomer of Neu5Ac and N-glycoly-neuraminic acid were identified. Through these results, it was confirmed that it is possible to separate sialic acid from EBN extract with efficient and high yield when using ABT.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.281-282
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• 2009

• Journal of Welding and Joining
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• v.27 no.5
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• pp.42-48
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• 2009

Pipe welding is used in various ranges such as civil engineering and ship building engineering. Until now, many technicians work for pipe welding manually under harmful, dangerous and difficult conditions. So it is necessary to install automation process. For automation pipe welding, relation between welding parameters & bead shape should be considered. Using this relation, bead shape could be expected from welding parameters. FCAW was used in this study. Instead of pipe workpiece, fillet joint plate is used, which were inclined 0,45,90,135,180 degree. By analyzing between welding parameters (current, welding speed, voltage) and bead shape parameters with non-linear multiple regression, bead shape parameters could be expected. Piecewise Cubic Hermite Interpolation was used to expect smooth curved bead shape with bead shape parameters. From these processes, bead shape could be expected from welding parameters.

• Transactions of Materials Processing
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• v.14 no.1 s.73
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• pp.21-28
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• 2005

This paper is concerned with the quantitative effect of design parameters on a stamped part of the auto-body. The considered parameters in this paper are the blank holding force, the draw-bead force, the blank size which greatly affect the metal flow during stamping. The indicators of formability selected in this paper are failures such as tearing, wrinkling and the amount of springback. The stamping process of the front side inner member is simulated using the finite element analysis changing the design parameters. The numerical results demonstrate that the blank holding force cannot control the local metal flow during forming although it controls the overall metal flow. The modification of the initial blank size considering the punch opening line ensures the local wrinkling and reduces the amount of springback after forming. The restraining force of draw-bead controls the metal flow in the local area and reduces the amount of excess metal. It is noted that the parametric study of design parameters such as blank holding force, the blank size and the draw-bead are very important in the process design of the complicated member.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.189-193
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• 1997

Generally, though we use the vision sensor or arc sensor in welding process, it is difficult to define the welding parameters which can be applied to the weld quality control. Especially, the important parameters is Arc Voltage, Welding Current, Welding Speed in arc welding process and they affect the decision of weld bead shape, the stability of welding process and the decision of weld quality. Therefore, it is difficult to determine the unique relationship between the weld bead geometry and the combination of various welding condition. Due to the various difficulties as mentioned, we intend to use Fuzzy Logic and Neural Network to solve these problems. Therefore, the combination of Fuzzy Logic and Neural network has an effect on removing the weld defects, improving the weld quality and turning the desired weld bead shape. Finally, this system can be used under what kind of welding process adequately and help us make an estimate of the weld bead shape and remove the weld defects.