• Journal of Welding and Joining
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• 제28권5호
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• pp.86-92
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• 2010

In GMAW processes, bead geometry is a criterion to estimate welding quality. Bead geometry is affected by welding current, arc voltage, welding speed, shielding gas and so on. Thus the welding condition has to be selected carefully. In this paper, an experimental method for the selection of optimal welding condition was proposed in the root pass welding which was done along the GMA 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. Through the experiments, the target values of the back bead width and the height were chosen as 4mm and 1mm respectively for the V-grooved butt weld joint. 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.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 추계학술대회 논문집
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• pp.298-303
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• 1997

Over the last few year, there has been a growing interest in quantitative representation of heat transfer phenomena in weld pools in order to relate the processing conditions to the quality of the weldment produced and to use this information for the optimisation and robotization of the welding process. Normally, a theoretical model offers a powerful alternative to check out the physical concepts of the welding process and to calculate the effects of varying any of parameters. To solve this problem, a transient 2D(two-dimensional) heat conduction were developed for determining bead geometry and temperature distribution for the GMA welding process. The equation was solved using a general thermofluid-mechanics computer program, PHOENICS code, which is based on the SIMPLE algorithm. The simulation results showed that the calculated bead geometry from the developed models reasonablely agree with the experiment results.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.111-116
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• 1999

Over the last few years, there has been a growing interest in quantitative representation of heat transfer and fluid flow phenomena in weld pools in order to relate the processing conditions to the quality of the weldment produced and to use this information for the optimization and robotization of the welding process. Normally, a theoretical model offers a powerful alternative to estimate the important input parameters and to calculate the effects of varying any of parameters. To solve this problem, a transient 2D(two-dimensional) heat conduction and a transient 2D axisymmetric heat and fluid model were developed for determining weld bead geometry and temperature distribution for the GMA(Gas Metal Arc) welding process. The equation was solved using a general thermofluid-mechanics computer program, PHOENICS code, which is based on the SIMPLE algorithm. The simulation results showed that the calculated bead geometry from two developed models reasonably agree with the experiment result.

• Journal of Welding and Joining
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• 제15권2호
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• pp.72-80
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• 1997

The spatter generation rate of GMA welding with $CO_2$ gas shielding was measured with the change of welding conditions such as wire feeding rate and welding voltage and then the results were analized with the accompanying changes in metal transfer mode and in bead geometry. The spatter generation rate (SGR) was relatively low not only wit the short circuit transfer but with the truely globular transfer mode. However, the SGR resulted with the mixed mode were consistantly high. The resultant wave pattern of mixed mode was due to the coexistance of short-circuit and globular transfer and characterized by the frequent appearance of instantaneous short circuit. Considering the result of SGR and that of bead geometry, it could be concluded that when the wire feeding rate (or welding current) was either low or high, the optimum bead shape could be obtained along with the low spatter generation. However, in the middle range of wire feeding rate, the optimum bead shape was only obtained in the mixed mode condition resulting in the high spatter generation.

• Journal of Welding and Joining
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• 제18권5호
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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.

• International Journal of Korean Welding Society
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• 제1권1호
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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.

• Journal of Welding and Joining
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• 제32권2호
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• pp.22-28
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• 2014

To enhance productivity and provide high quality production material in a GMA welding process, weld quality, productivity and cost reduction affects the number of process variables. In addition, a reliable welding process and conditions must be implemented to reduce weld structure failure. In various industries the welding process mathematical model is not fully formulated for the process parameter and on the welding conditions, therefore only partial variables can be predicted. The research investigates the interaction between the welding parameters (welding speed, distance between electrodes, and flow rate of shielding gas) and bead geometry for predicting the weld bead geometry (bead width, bead height). Taguchi techniques are applied to bead shape to develope curve equation for predicting the optimized process parameters and quality characteristics by analyzing the S/N ratio. The experimental results and measured error is within the range of 10% presenting satisfactory accuracy. The curve equation was developed in such a way that you can predict the bead geometry of constructed machinery that can be used for making tandem welding process.

• 한국생산제조학회지
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• 제22권1호
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• pp.22-28
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• 2013

Robotic GMA (Gas Metal Arc) welding process is one of widely acceptable metal joining process. The heat and mass inputs are coupled and transferred by the weld arc to the molten weld pool and by the molten metal that is being transferred to the weld pool. The amount and distribution of the input energy are basically controlled by the obvious and careful choices of welding process parameters in order to accomplish the optimal bead geometry and the desired quality of the weldment. To make effective use of automated and robotic GMA welding, it is imperative to predict online faults for bead geometry and welding quality with respect to welding parameters, applicable to all welding positions and covering a wide range of material thickness. MD (Mahalanobis Distance) technique was employed for investigating and modeling the GMA welding process and significance test techniques were applied for the interpretation of the experimental data. To successfully accomplish this objective, two sets of experiment were performed with different welding parameters; the welded samples from SM 490A steel flats. First, a set of weldments without any faults were generated in a number of repeated sessions in order to be used as references. The experimental results of current and voltage waveforms were used to predict the magnitude of bead geometry and welding quality, and to establish the relationships between weld process parameters and online welding faults. Statistical models developed from experimental results which can be used to quantify the welding quality with respect to process parameters in order to achieve the desired bead geometry based on weld quality criteria.

• 한국생산제조학회지
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• 제7권6호
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• pp.57-63
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• 1998

An adaptive control in the robotic GMA welding is employed to monitor information about weld characteristics and process parameters as well as to modify those parameters to hold weld quality within acceptable limits. Typical characteristics are the bead geometry, composition, microstructure, appearance, and process parameters which govern the quality of the final weld. The main objectives of this thesis are to realize the mapping characteristics of bead width through learning. After learning, the neural estimation can estimate the bead width desired form the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead width with reasonable accuracy and guarantee the uniform weld quality.

• Journal of Welding and Joining
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• 제35권1호
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• pp.16-25
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• 2017

Gas Metal Arc Welding is a widely used process in Industry due to its high productivity and potential to automation. The present study investigates the effects of the welding speed, arc voltage, welding current and shielding gas on the bead geometry for a low-carbon steel. The Response Surface Methodology (RSM) is used to choose an experimental design and perform test runs accordingly in order to produce mathematical models predicting the geometry, the hardness and the heat input of the bead as functions of the welding parameters. The direct and interaction effects of the four welding parameters are represented graphically and allow to determine an optimum set of welding parameters.