• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.49-60
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• 1999

This paper addresses a welding task sequencing for robot arc welding process planning. Although welding task sequencing is an essential step in the welding process planning, it has not been considered through a systematic approach, but it depends rather on empirical knowledge. Thus, an effective task sequencing for robot arc welding is required. Welding perations can be classified by the number of welding robots. Genetic algorithms are applied to tackle those welding task sequencing problems. A genetic algorithm for traveling salesman problem (TSP) is utilized to determine welding task sequencing for a MultiWeldline-SingleLayer problem. Further, welding task sequencing for multiWeldline-MultiLayer welding is investigated and appropriate genetic algorithms are introduced. A random key genetic algorithm is also proposed to solve multi-robot welding sequencing : MultiWeldline with multi robots. Finally, the genetic algorithm are implemented for the welding task sequencing of three dimensional weld plate assemblies. Robot welding operations conforming to the algorithms are simulated in graphic detail using a robot simulation software IGRIP.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 춘계학술대회 논문집
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• pp.1219-1220
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• 2012

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.124-132
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• 2001

Autonomous of welding process in shipyard is ultimately necessary., since welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding robot that can navigate autonomously within the enclosure needs to be developed. To achieve the welding ra나, the robotic welding systems needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with work environmental map. At the same time a strategy for environment recognition for welding mobile robot is proposed in order to recognize the work environment efficiently. The design of the sensor system, the algorithm for sensing the structured environment, and the recognition strategy and tactics for sensing the work environment are described and dis-cussed in detail.

• International Journal of Korean Welding Society
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• 제2권2호
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• pp.47-50
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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.

• International Journal of Korean Welding Society
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• 제3권1호
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• pp.8-16
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• 2003

A major concern in Gas Metal Arc (GMA) welding process is the determination of welding process variables such as wire diameter, gas flow rate, welding speed, arc current and welding voltage and their effects on the desired weld bead dimensions and shape. To successfully accomplish this objective, 81 welded samples from mild steel AS 1204 flats adopting the bead-on-plate technique were employed in the experiment. The experimental results were used to develop a mathematical model to predict the magnitude of bead geometry as follows; weld bead width, weld bead height, weld bead penetration depth, weld penetration shape factor, weld reinforcement shape factor, weld bead total area, weld bead penetration area, weld bead reinforcement area, weld bead dilution, length of weld bead penetration boundary and length of weld bead reinforcement boundary, and to establish the relationships between weld process parameters and bead geomery. Multiple regression analysis was employed for investigating and modeling the GMA process and significance test techniques were applied for the interpretation of the experimental data.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2002년도 추계학술대회 논문집
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• pp.323-328
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• 2002

Since the pre flex beam is fabricated by welding, the precompressive stresses that should occur over the concrete pier are diminished by the welding residual stresses. Therefore the welding residual stresses must be relieved during the fabrication. So the analysis and examination of the accurate welding residual stress distribution characteristic are necessary. On this study, accurate distribution of welding residual stress of preflex beam is analyzed by finite element method.

• 한국정밀공학회지
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• 제14권3호
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• pp.41-49
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• 1997

Laser spot welding offers a unique combination of high speed. precision and low heat distortion, compared with conventional resistance spot welding. This combinatin of advantages is especially attractive for the automotive industry. Until now automobile fabrication is widely used resistance spot welding, however, because of geometric and structural problem, spot welding is required many welding machine in that reason by substituting spot welding with laser welding, it save the equipment cost. In the present study we measured ultimate strength and observed bead cross section of laser welded specimen and compared with that of the resistance spot welding results in order to adapt laser welding in automobile industry. Also for strength esti- mation we calculated the residual stress of laser welded zone. All calculations are performed with the ABAQUS code on a workstation.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2010년도 춘계학술발표대회 초록집
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• pp.53-53
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• 2010

The purpose of this paper is to propose a mathematical model of welding current for the P-GMAW by modifying the well known GMAW model. Welding power circuit is simply modeled as a RL electric circuit and solved as an ODE equation. The welding current depends on the joint shape, molten pool and welding parameters. To compare the molten pool effect to the welding current, CFD numerical simulation technique was adopted. Welding experiment is also conducted with the same welding parameters as used in numerical simulations to verify the proposed welding current model. The current model which is considered molten pool shape, is more fit to experiment result.

• 대한조선학회논문집
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• 제56권6호
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• pp.473-479
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• 2019

Welding is one of the most popular joining methods and most welding quality estimation methods are executed using joined material. This paper propose welding quality estimation methods using dynamic current, voltage and resistance which are obtained during welding in real time. There are many kinds of welding method. Among them, we focused on the projection welding and gathered dynamic characteristics from two different types of projection welding. For image learning, graphs are drawn using obtained current, voltage and resistance, and the graphs are converted to images. The images are labeled with two sub-categories - normal and defect. For deep learning of images obtained from welding, Convolutional Neural Network (CNN) is applied, and Tensorflow was used as a framework for deep learning. With two resistance welding test datasets, we conclude that the Convolutional Neural Network helps in predicting the welding quality.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.185-190
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• 2003

At the present, a stud bolt welding was achieved by the manual method. The manual method caused many problems of work evasion. In order to work out these problems, an automatic welding system is designed for a stud bolt welding system. The system is composed of articulated type welding robot, stud gun, stud feeder, stud controller and various jig.