• Journal of Welding and Joining
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• v.24 no.5
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• pp.37-42
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• 2006

The robotic arc welding is widely employed in the fabrication industry fer increasing productivity and enhancing product quality by its high processing speed, accuracy and repeatability. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. In this paper, the possibilities of the Infrared camera in sensing and control of the bead geometry in the automated welding process are presented. Both bead width and thermal images from infrared thermography are effected by process parameters. Bead width and isotherm radii can be expressed in terms of process parameters(welding current and welding speed) using mathematical equations obtained by empirical analysis using infrared camera. A linear relationship exists between the isothermal radii producted during the welding process and bead width.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.66-76
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• 2002

Automated welding and soldering are an important manufacturing issue in order to lower the cost, increase the quality, and avoid labor problems. An off-line programming, OLP, is one of the powerful methods to solve this kind of diversity problem. Unless an OLP system is ready for the path optimization in welding and soldering, the waste of time and cost is unavoidable due to inefficient paths in welding and soldering processes. Therefore, this study attempts to obtain path optimization using a genetic algorithm based on artificial intelligences. The problem of welding path optimization is defined as a conventional TSP (traveling salesman problem), but still paths have to go through welding lines. An improved genetic algorithm was suggested and the problem was formulated as a TSP problem considering the both end points of each welding line read from database files, and then the transit problem of welding line was solved using the improved suggested genetic algorithm.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.687-697
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• 2022

An automated system is needed for the effectiveness of non-destructive testing. In order to utilize the radiographic testing data accumulated in the film, the types of welding defects were classified into 9 and the shape of defects were analyzed. Data was preprocessed to use deep learning with high performance in image classification, and a combination of one-stage/two-stage method and convolutional neural networks/Transformer backbone was compared to confirm a model suitable for welding defect detection. The combination of two-stage, which can learn step-by-step, and deep-layered CNN backbone, showed the best performance with mean average precision 0.868.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.556-559
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• 2008

In this study, an automated ultrasonic testing system and post signal and image processing techniques are developed in order to construct ultrasonic flaw images in weldments. The automated ultrasonic testing system developed in the present study adopted an 8 channel pulser/receiver-ADC unit and a 2 axis motion driving unit and the post signal and image processing algorithms are built into the system program of the automated ultrasonic testing system.

• Journal of Welding and Joining
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• v.24 no.1
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• pp.71-76
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• 2006

In this study, the microstructure and mechanical properties of spot friction stir welded A 5052 alloy were investigated. Especially, the effect of insertion depth of welding tool on microstructural changes and mechanical properties was investigated in order to obtain the optimum spot friction stir welding condition. The lap shear load of spot friction stir welded A 5052 alloy plates showed lower value at the shallowest insertion depth and increased with tool insertion depth. At 1.6mm, the maximum value of 3.35 kN was obtained, and then dropped to lower load when the insertion depth was deeper. Spot friction stir welded joints showed shear fracture mode at shallower insertion depths and fracture mode changed to plug fracture mode as the insertion depth was deeper.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.2
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• pp.38-43
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• 2015

Tungsten inert gas (TIG) welding is commonly used in industries that require airtightness, watertightness, oiltightness, and precision. It is a non-consumable welding method that is commonly used for the welding of non-ferrous metals, but it can be used to weld most metals. The methods of TIG welding can be divided into three types. The first, manual welding is done directly on the metal by a welder with a torch. The second, semi-automatic welding, gets help from a material supplying machine, but it is conducted by a welder. Lastly, automated welding is conducted fully by a machine during its process and operation. Depending on the selection of electrode, the amount of heat that is applied to the base material and the electrode rod changes and makes the shape of welded parts different. A direct-current positive electrode was used for this study. Through the change of shielding gas type on a structural steel (SS-400) that is commonly used in industry, the composition and shape changes in welded parts were detected after welding. The heat-affected area, hardness value, and tensile strength were also identified through hardness testing and tensile testing. In this study, it was found that the higher hardness value of the heat-affected is, the weaker the tensile strength becomes.

• Journal of Welding and Joining
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• v.35 no.2
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• pp.43-51
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• 2017

The automatic welding systems, have received much attention in recent years, because they are highly suitable not only to increase the quality and productivity, but also to decrease manufacturing time and cost for a given product. Automatic welding work in semiconductor or space industry to be carried out in pipe line and butt joint mostly and plasma arc welding(PAW) is actively applied. To get the desired quality welds in automated welding system is challenging, a mathematical model is needed that has complete control over the relevant process parameters in order to obtain the required mechanical properties. However, 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. Therefore, this paper investigates the interaction between the welding parameters and mechanical properties for predicting the weld bead geometry by analyzing the S/N ratio.

• Journal of Welding and Joining
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• v.26 no.5
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• pp.29-35
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• 2008

In this paper concentrate on the comparison of the thermal and mechanical characteristics in Butt joint of ship structure AH32 steel by using hybrid welding and conventional SAW. For this purpose, fundamental welding phenomena of hybrid process using $CO_2$ Laser and MIG is investigated by the experiments and characteristics of thermal and welding residual stress distribution of welded joint in SAW and hybrid welding are understood from the result of FE numerical simulation and experimental values. From the result of this study, it is understood that Laser-MIG hybrid welding have high potential, make substantial saving of time and manufacturing cost and may proves its self robust in the butt joining of thick AH32 steel ship structural plate in the near future.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. 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.