• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

• International Journal of Korean Welding Society
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• v.3 no.2
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• pp.15-23
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Welding and Joining
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• v.18 no.5
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Proceedings of the KWS Conference
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• 2003.05a
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• pp.172-175
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. According to the conventional full factorial design, in order to find the optimal welding conditions, 16,384 experiments must be performed. The genetic algorithm however, found the near optimal welding conditions from less than 60 experiments.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.69-86
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• 2020

Purpose: This study aims to determine the optimal conditions for the spot welding process that mechanically connects the case of a cylindrical secondary battery and the negative tab. Methods: We use 33 factorial design to derive the optimal conditions for the spot welding process. The pulling strength, the cross-sectional area of nugget, and the shock test life are selected as response variables, which can represent the resistance welding quality. The input variables are selected as the welding time, welding voltage, and pressure, which are the controllable factors in the spot welding process. Results: The main effects of welding time and welding voltage and the interaction effect of welding time and welding voltage are significant. Conclusion: The optimal conditions for the spot welding process to mechanically join the negative electrode tab of the cylindrical secondary battery and the battery case are developed. The result shows that the pulling strength is increased by 44% compared to before improvement under optimal conditions.

• Proceedings of the KWS Conference
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• 1999.05a
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• pp.215-218
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• 1999

With increasing demand of energy saving, -many efforts were made to employ aluminium alloys in the automobile industry. Especially, resistance spot welding has been widely used in the steel metal joining process because of its high productively and convenience. In this paper, spot weldability of 7075-T6 aluminium thin sheets for various welding conditions were examined by series of experiments. The tensile shear strength and microstructure of welded specimens was observed, and The optimal welding conditions were found for each welding conditions.

• Journal of Welding and Joining
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• v.5 no.3
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• pp.19-27
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• 1987

This paper presents the weldability for cold pressure but welding method in junction of dissimilar metals each other. Although the weldability between the same aluminium metal plate welding has been studied, the study of itthe rod of aluminium and coper has not fully been investigated. The purpose is to suggest the optimal conditions on the rod of those under above method. To obtain the optimal conditions, associated experiments were performed in a various welding parameters. Consequently, it was proved that the mechanical properties such as tensile strength, hardness and bending strength could be obtained excellent particularly under the welding conditions; pressure is $(32~39) {\times} 10^3/kg/cm^2$, time is beyond 70 seconds, stage is higher than fifth stage.

• Journal of Welding and Joining
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• v.21 no.2
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• pp.76-81
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• 2003

Due to the environmental problem, automotive companies are trying to reduce the weight of car body. Therefore, WP(Transformation Induced Plasticity) steels, which are hish strength and ductility have been developed. The application of TRIP steel to the members has been reported to increase the energy absorption capability. Welding process is a complex process; therefore deciding the optimal welding conditions is an effective method on the basis of the experimental data. However, using a trial-and-error method from the beginning in such a wide area, in order to decide the optimal conditions requires too many numbers of experiments. To overcome these problems and to decide the optimal conditions, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are for 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. The introduced method was applied to the resistance spot welding process of the TRIP steel and the welding parameters were optimized. (Received December 6, 2002)

• Journal of Welding and Joining
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• v.24 no.5
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• pp.29-36
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• 2006

In this study, an experimental method for the selection of optimal welding condition was proposed in the fillet weld which was done over the tack weld. This method used the response surface analysis in which the leg length and the reinforcement height were chosen as the quality variables of the weld bead profile. The overall desirability function, which was combined desirability function fur the two quality variables, was employed as the objective function for getting the optimal welding condition. In the experiments, the target values of the leg length and the reinforcement height are 6m and zero respectively for the horizontal fillet weld of 10mm thickness mild steel. The optimal welding conditions could predict the weld bead profile(leg length and reinforcement height) as 6.00mm and 0.19mm without tack weld and 6.00mm and 0.48mm with tack weld. from a series of welding test, it was revealed that a uniform weld bead can be obtained by adopting the optimal welding condition which was determined according to the method proposed.

• Journal of Welding and Joining
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• v.27 no.1
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• pp.95-101
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• 2009

In case of manufacturing the high quality welds or pipeline, the full penetration weld has to be made along the weld joint. Thus the root pass welding is very important and has to be selected carefully. In this study, an experimental method for the selection of optimal welding condition was proposed in the root pass welding which was done along the V-grooved butt weld joint. This method uses the response surface analysis in which the width and height of back bead were chosen as the quality variables of the weld. The overall desirability function, which is the combined desirability function for the two quality variables, was used as the objective function for getting the optimal welding condition. In the experiments, the target values of the back bead width and the height are 6mm and zero respectively for the V-grooved butt weld joint of 8mm thickness mild steel. The optimal welding conditions could predict the back bead profile(bead width and height) as 6.003mm and -0.003mm. From a series of welding test, it was revealed that a uniform and full penetration weld bead can be obtained by adopting the optimal welding condition which was determined according to the method proposed.