• Proceedings of the KWS Conference
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• 2002.10a
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• pp.366-371
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• 2002

Because of the environmental problems, automotive companies are trying to reduce the weight of car body. Therefore, TRIP(TRansformation Induced Plasticity) steels, which have high strength and ductility have been developed. Welding process is a complex process; therefore deciding the optimal welding conditions on the basis of experimental data is an effective method. However, trial-and-error method to decide the optimal conditions requires too many experiments. To overcome these problems, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are used in the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. This method was applied to the resistance spot welding process of the TRIP steel to optimize the welding parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.166-166
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld qualify is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.5
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• pp.81-87
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• 2015

In this paper, the finite element method was used for the flow and strength analysis of aluminum alloy under friction stir welding. The simulations were carried out using Sysweld s/w, and the modeling of the sheet was executed using Unigraphics NX6 s/w. The welding variables for the analysis were the shoulder diameter, rotating speed, and welding speed of the tool. Additionally, a three-way factorial design method was applied to confirm the effect of the welding variables on the flow and strength analysis with variance analysis. From these results, the rotating speed had the greatest influence on the maximum temperature, and the maximum temperature was $578.84{\pm}12.72$ at a confidence interval of 99%. The greater the rotating speed and shoulder diameter, the greater the difference between maximum and minimum temperature. Furthermore, the shoulder diameter had the largest influence on von Mises stress, and the von Mises stress was $184.54{\pm}12.62$ at a confidence interval of 99%. In addition to the increased shoulder diameter, welding speed, and rotating speed of the tool increased the von Mises stress.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.132-139
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• 2002

In GMAW(Gas Metal Arc Welding) processes, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality. Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWD (contact-tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using neuro-fuzzy algorithm. Neural networks was applied to design FL(fuzzy logic). The parameters of input membership functions and those of consequence functions in FL were tuned through the method of learning by backpropagation algorithm. Bead geometry could be reasoned from welding current, arc voltage, travel speed on FL using the results learned by neural networks. On the developed inference system of bead geometry using neuro-furzy algorithm, the inference error percent of bead width was within $\pm$4%, that of bead height was within $\pm$3%, and that of penetration was within $\pm$8%. Neural networks came into effect to find the parameters of input membership functions and those of consequence in FL. Therefore the inference system of welding quality expects to be developed through proposed algorithm.

• Proceedings of the KWS Conference
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• 2001.10a
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• pp.184-186
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• 2001

Quality estimation of the weld has been one of the important issues in RSW which is a main process of the sheet metal fabrication in auto-body industry. It was well known that among the various welding process variables, dynamic resistance has a close relation with nugget formation. In this study, a new quality estimation algorithm is developed with the primary dynamic resistance measured at welding machine timer. For this, Back propagation algorithm of neural network is used.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.1-11
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• 2022

In this study, an electric resistance dual-spot welding process using a copper electrode inserted in a heating electrode is suggested for the spot welding of AZ31 magnesium sheets. This spot-welding process involves two heating methods for welding at the interfacial zone between the magnesium sheets, one of which is the heating method by thermal conduction from the heating electrode heated by the welding current induced to the steel electrode, and the other heating method uses the electric resistance between the contacted surfaces of the two sheets by the welding current induced to the copper electrode. This welding process includes the welding variables, such as the current induced in the heating electrode and the copper electrode, and the outer diameters of the heating electrode. This is because the heat conducted from the heating electrode can be maintained at a higher temperature in the welding zone, which has a slow cooling effect on the nugget of the melted metal after the welding step. The pressure exerted during the pressing of the magnesium sheets by the heating electrode can be increased around the nugget zone at the spot-welding zone. Thus, it not only reduces the warping effect of the elastoplastic deformation of sheets, but also the corona bond can make it less prone to cracking at the welded zone, thereby reducing the number of nuggets expelled out of the corona bond. In conclusion, it was known that an electric resistance dual spot welding process using the copper electrode inserted in the heating electrode can improve the welding properties in the electric resistance spot welding process of AZ31 magnesium sheets.

• Journal of the Korean Society of Industry Convergence
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• v.14 no.1
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• pp.15-21
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• 2011

Welding variables and conditions in gas metal arc welding (GMAW) effect on the quality and productivity of the weld, extensive research efforts have been made to analyze the effect of the welding variables and conditions. In this study dynamic behavior of GMAW system is investigated using the characteristics of the power supply, wire and welding arc. Characteristic equation of wire is modified to include the effect of droplets attached at the electrode tip. The dynamic characteristics of arc length, current, voltage with respect to the step, ramp inputs of CTWD was simulated. From results of simulation, some predictions about dynamic characteristics of GMAW and welding process are available. The proposed simulator and results appear to be utilized to determine the proper welding conditions, to be improved by considering power supply dynamic characteristics.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.2
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• pp.207-213
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• 2001

Welding variables and condition in gas metal arc welding (GMAW) effect on the weld quality and productivity, extensive research efforts have been made to analyze the welding variables and conditions. In this study dynamic behavior of GMAW system is investigated using the chararcteristic equations of the power supply. wire and welding arc. Characteristic equation of wire is modified to include the effect of droplets attached at the electrode tip. The dynamic characteristics of arc length, current, voltage with respect to the step, ramp inputs of CTWD was simulated. From results of simulation, some predictions about dynamic characteristics of GMAW and welding process are available. The proposed simulator and results appear to be utilized to determine the proper welding conditions, to be improved by considering power supply dynamic characteristics.

• Transactions of Materials Processing
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• v.19 no.8
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• pp.452-459
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• 2010

It was investigated that two plates of aluminum can be welded by hot extru-shear welding process with extru-shear welding dies, and that the welding strength and metal flow on the welding section were analyzed by computer simulation according to the welding variables such as inclined angle of cutter and overlapped length of plates and temperature of plates. It was known by computer simulation that welding strength on the welding section of plates could be influenced by the inclined angle of cutter and overlapped length of plates and temperature of plates. And it was known by experiments that two plates of aluminum can be welded on the end sections by hot extru-shear welding process using extru-shear welding dies, and that welding strength is the highest when inclined angle of dies is $70^{\circ}$, and overlapped length is 1.2 mm, and temperature is $520^{\circ}$, when aluminum 5052 two plates with 1.6 mm thickness are used as welding material.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.301-302
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• 2006

In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.