• Proceedings of the KWS Conference
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• 1999.10a
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• pp.202-204
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• 1999

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.109-112
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• 2005

Friction welding is welding method to use frictional heat of two material. A defect of friction welding is that create flash. The flash is part that must have cut after welding finished. But the welding part with flow gallery by friction welding can't cut flash. Therefore the welding part with flow gallery was designed with no effect in flow. In this research, decide the welding shape parameter of welding part with flow gallery and do friction welding analysis. In friction welding analysis, must input necessary S-S curve, friction coefficient by temperature change, upset pressure, RPM etc. According to analysis result, decided the optimal shape of welding part with no effect in flow.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.5
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• pp.436-442
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• 2013

Friction welding is a very useful joining process to weld metals which have axially symmetric cross section. In this paper, the feasibility of industry application was determined by analyzing the mechanical properties of weld region for a specimen of tube-to-tube shape for excavator hose nipple with friction welding, and optimized welding variables were suggested. In order to accomplish this object, friction heating pressure and friction heating time were selected as the major process variables and the experiment was performed in three levels of each parameter. An acoustic emission(AE) technique was applied to evaluate the optimal friction welding conditions nondestructively. AE parameters of accumulative count and event were analyzed in terms of generating trend of AE signals across the full range of friction weld. The typical waveform and frequency spectrum of AE signals which is generated by friction weld were discussed. From this study the optimal welding variables could be suggested as rotating speed of 1300 rpm, friction heating pressure of 15 MPa, and friction heating time of 10 sec. AE event was a useful parameter to estimate the tensile strength of tube-to tube specimen with friction weld.

• Journal of Welding and Joining
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• v.24 no.5
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• pp.67-73
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• 2006

Laser welding is suitable for welding to the aluminum alloy sheet. In order to apply the aluminum laser welding to production line, parameters should be optimized. In this study, the optimal welding condition was searched through the genetic algorithm in laser welding of AA5182 sheet with AA5356 filler wire. Second-order polynomial regression model to estimate the tensile strength model was developed using the laser power, welding speed and wire feed rate. Fitness function for showing the performance index was defined using the tensile strength, wire feed rate and welding speed which represent the weldability, product cost and productivity, respectively. The genetic algorithm searched the optimal welding condition that the wire feed rate was 2.7 m/min, the laser power was 4 kW and the welding speed was 7.95 m/min. At this welding condition, fitness function value was 137.1 and the estimated tensile strength was 282.2 $N/mm^2$.

• 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.

• Journal of Welding and Joining
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• v.29 no.6
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• pp.45-48
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• 2011

In this research, laser welding of automotive transmission components was investigated to replace electron beam welding which is normally conducted under vacuum condition. Fiber laser welding was applied to the automotive transmission components - hub clutch and annulus gear. In the component welding, the laser welding parameters were optimized to eliminate spatters and the end crater. By applying laser welding to the transmission parts, the process time could be reduced up to 70% compared with the current electron beam welding process.

• 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.

• Proceedings of the KWS Conference
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• 2004.05a
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• pp.209-211
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• 2004

자동차 차체의 조립공정에서 주로 사이리스터 방식의 저항 점 용접기를 이용해 용접을 하고 있으나, 최근에는 인버터방식을 이용하려는 시도가 진행되고 있다. (중략)

• Laser Solutions
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• v.14 no.3
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• pp.12-16
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• 2011

In automotive industry, because of the consideration of fuel economy, lightweight alloys have been adopted and are expected to be extensively used in the future. Magnesium alloys are among the promising materials, due to their lightweight and good mechanical properties. This study is related to the laser weldability of AZ31B magnesium alloy, an all-purpose wrought alloy with good strength and ductility. A 4kW Nd:YAG laser was used to join AZ31B sheet, and the effects of welding parameter on the quality of lap-welded joints were investigated. As a result of this study, the optimal condition was obtained, and the effect of gap distance was also revealed on the porosity control.