• Journal of Welding and Joining
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• v.9 no.3
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• pp.41-51
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• 1991

The thermomechanical coupling phenomena in the resistance welding process is complicated due to interactions of mechanical, thermal and electrical factors. Although experimental investigations of resistance spot welding have been carried out, but there are a few by computer simulation. so the purpose of this research is to decrease the time and cost much required in experimental investigation by carrying out the analysis of the resistance spot welding process through computer simulation based on the finite element method. The tool used in the computer simulation is the commercial ANSYS program package. A two dimensional axisymetric model is used to simulate the resistance spot welding for two stainless steel sheets of equal thickness and parametric study is carried out for variable welding current, workpieces of unequal thickness and dissimilar materials. The results from the computer simulation are in good agreement with the experimental one. Through these results, such items as stress distribution, temperature profiles, thermal expansion and weld nugget formation are predicted. Reliability and applicability of finite element models have been demonstrated to simulate and to analyze the resistance spot welding process.

• Transactions of Materials Processing
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• v.27 no.3
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• pp.145-153
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• 2018

Magnesium material could be widely used in the automotive industry because of its high strength to weight ratio, but the electric resistance spot welding process of magnesium sheets is difficult because of its low electric resistance and high thermal conduction and thermal expansion. For this reason, an electric resistance surface friction spot welding process using rotating dies is suggested for the spot welding of magnesium metal sheets. This welding method can be characterized by three heating methods: (1) electric resistance heating on contacted surface, (2) surface friction heating by rotating dies, and (3) thermal conduction heating from heated steel electrodes, for the fusion of metal at the interfacial zone between the two magnesium sheets. This welding process also has variables to explore, such as welding currents, diameters of the steel electrode, and rotating dies. It was found that the welding strength could reach industrial requirements by applying a welding current of 11.0kA, with steel electrodes of 12mm diameter, with rotating dies of 4.4 mm diameter, under the condition of a revolution speed of 1200rpm of rotating dies, for the surface friction spot welding process of AZ31 magnesium alloy sheets of 1.4mm thickness.

• Journal of Welding and Joining
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• v.15 no.6
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• pp.116-123
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• 1997

In GMA welding processes, bead contour and penetration patterns are criterion to estimate weld quality. Bead geometry is commonly defined with width, height and depth. When weaving is taken into account, selection of welding conditions is known to be difficult. Thus, empirical or trial-and-error method are usually introduced. This study examined the correlation of welding process variables including weaving parameters with bead geometry using srtificial neural networks(ANN). The main task of the Ann estimator is to realize the mapping characteristics from the sampled welding process variables to the actual bead geometry through training. After the neural network model is constructed, welding process variables for desired bead geometry is selected by inverse model. Experimental varification of the inverse model is conducted through actual welding.

• Proceedings of the KWS Conference
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• 2005.06a
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• pp.226-228
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• 2005

Of typical welding techniques, to employ the heat for joining process is the most commonly used welding process. But there arise difficulties when this process is applied to light weight alloys such as Aluminium alloy. In this respect, Friction Stir Welding(FSW), a solid-state joining process, is the most effective welding technique with significant potential for various industrial applications. In this study, the characteristics of lapping FSW Al 5052 alloy are shown under a variety of welding parameters such as the rotation speed of FSW tool and welding velocity. Conclusively, the welding properties of lapping FSW Al 5052 were found to be dominated by the deformation of non-joining area near the welding nugget rather than other factors such as the thermal input.

• International Journal of Korean Welding Society
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• v.1 no.2
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• pp.7-11
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• 2001

Almost every die for automobiles must be corrected or remodeled for minor geometrical changes or fur better hardness characteristics by an arc welding process. Although many other kinds of arc welding processes have been automated with robots, the molten metal deposition process for die remodeling still depends entirely on experienced welders. In this study, a database for bead shapes with respect to welding parameters is constructed through experiments to automate molten metal deposition by the arc welding process. Changes in the welding parameters for inclined base metal are studied to consider the effect of die geometries on the welding process.

• Journal of Welding and Joining
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• v.21 no.5
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• pp.561-567
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• 2003

For construction of I-beam steel structures, a fillet welding is one of the main manufacturing process. However, this welding process cause some problems associated with welding residual stress and welding deformation that are harmful to the safety of structures. Accordingly, this study clarified the creation mechanism of the welding deformation on I-beam steel structure from the experimental results given by the FEM method. To prevent or minimize the longitudinal bending deformation, first of all, a field supervision is necessary to observe the optimal groove design. Secondly, the welding order for cooling weld zone is needed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.93-100
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• 2021

Copper sheets has been used widely in electric and electron industry fields because they have good electric and heat conduction property of the material. And, in order to bond copper material, a kind of soldering process is generally used. But, because it is difficult to bond by soldering between overlapped thin copper sheets, so, another kind of brazing bonding process can be used in that case. But, because the brazing process needs wide bonding area, it needs heat treatment process in electric furnace. Generally, for spot welding of sheets, a conventional electric Resistance Spot Welding process(RSW) has been used, it has welding characteristics using contact resistance heating induced by electric current flow between sheets. But, because copper sheets has the low electric resistance, it is difficult to weld by electric resistance spot welding. So, in this study, an electric Resistance heated Surface Friction Spot Welding process(RSFSW) is suggested and is testified for the spot welding ability of thin copper sheets. It is known from the experimental results and simulation that the suggested spot welding process will be able to improve the spot welding ability of copper sheets by the combined three kinds of heating generated by surface friction by rotating pin, and conducted from heated steel electrode, and generated by contact resistance of electricity.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1054-1061
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• 2011

GMA welding process is a production process to improve productivity for the provision of higher quality of material, These includs numerous process variables that could affect welding quality, productivity and cost savings. Recently, the welding part of construction equipment had frequent failure of major components in the welding part of each subsidiary material due to shock which is very poor according to the welding part. Therefore, the implementation of sound welding procedure is the most decisive factor for the reliability of construction machinery. The data generated through experimens conducted in this study has validated its effectiveness for the optimization of bead geometry and process variables is presented. The criteria to control the process parameters, to achieve a healthy bead geometry. This study has developed mathematical models and algorithms to predict or control the bead geometry in GMA fillet welding process.

• International Journal of Korean Welding Society
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• v.1 no.2
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• pp.12-17
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• 2001

With the advance of the robotic welding process, procedure optimization that selects the welding procedure and predicts bead width that will be deposited is increased. A major concern involving procedure optimization should define a welding procedure that can be shown to be the best with respect to some standard and chosen combination of process parameters, which give an acceptable balance between production rate and the scope of defects for a given situation. This paper presents a new algorithm to establish a mathematical model f3r predicting bead width through a neural network and multiple regression methods, to understand relationships between process parameters and bead width, and to predict process parameters on bead width for GMA welding process. Using a series of robotic arc welding, additional multi-pass butt welds were carried out in order to verify the performance of the neural network estimator and multiple regression methods as well as to select the most suitable model. The results show that not only the proposed models can predict the bead width with reasonable accuracy and guarantee the uniform weld quality, but also a neural network model could be better than the empirical models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.596-599
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• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. 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 research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.