• 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.

• 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.

• Journal of Welding and Joining
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• v.10 no.2
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• pp.32-42
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• 1992

A method of optimization of process parameters in Arc Welding has been discussed in this paper. The method of investigation is based on the numerical calculation of weld bead by a finite element method and non-linear optimization technique is applied to estimated the optimization process parameters from the numerical calculation. The common package program(ANSYS 4.4A) was used to obtain the process parameters for a thin plate arc welding (TIG, CO$_{2}$). The results on some test are satisfactory and the used method of this paper is a useful guide to the optimum welding condition.

• Journal of Ocean Engineering and Technology
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• v.13 no.3 s.33
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• pp.83-91
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• 1999

Taking a view of joining by welding the IN713C to SCM440 and SCM415 steel in production of turbochargers, the frictin welding process may be utilized as a new approach for joining them of other conventional welding processes. It is because the friction welding has more technical and technical and economic advantages than the other welding processes. As this welding process has the characteristics such as curtaliment of production time and materials and cost reduction, etc.. So, this paper deals with determining the preper friction welding condition and analyzing various mechanical properties of friction welded joints of the super heat resisting steel to alloy stee(IN713C to SCM440 and SCM415). And the in-process real-time weld quality evaluation technique by acoustic emission during friction welding of IN713C to SCM440 and SCM415 steels with higher confidence and relibility has been much required even though it might be the first trial approach for developing it. Then, this first study aimed to develop the optimization of dissimilar friction welding of heat resisting steels (INC713 to SCM440, SCM415) for turbine, considering on strength and toughness.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.123-130
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• 2006

In manufacturing, process automation and parameter optimization are required in order to improve productivity. Especially in welding process, productivity and weldablity should be considered to determine the process parameter. In this paper, optimization methodology was proposed to determine the welding conditions using the objective function in terms of productivity and weldablity. In order to conduct this, welding experiments were carried out. Tensile test was performed to evaluate the weldability. Neural network model to estimate tensile strength using the laser power, welding speed, and wire feed rate was developed. Objective function was defined using the normalized tensile strength which represented the weldablilty and welding speed and wire feed rate which represented the productivity. The optimal welding parameters which maximized the objective function were determined.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.180.6-180
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• 2001

Welding/soldering automation is one of the most important manufacturing issues 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 diver sity problem, Unless an OLP system is ready for the path optimization in welding/soldering, a waste of time and cost is unavoidable due to an inefficient path in welding/soldering processes. Therefore, this study attempts to obtain path optimization using a genetic algorithm based on artificial intelligences. The problem of the welding path optimization is defined as 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 ...

• Journal of Welding and Joining
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• v.15 no.4
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• pp.70-77
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• 1997

Welding is one of the most important and popular joining techniques employed in structures. In spite of, weld designs depend on the rules and regulations. Moreover, the study to optimize a shape of welding joint not may be sufficient and systematic on the theoretical and experimental sides. Therefore, in this study, a computer program based on thermal elasto plastic theory is developed for optimizing(minimizing) shape of weld joints. By the results, study is made on the characteristics of the distributions of welding residual stresses and plastic strains, and their production mechanisms. Also, Various kinds of tests are carried out to find out mechanical characteristics due to shape of weld joints. As a result of this optimization(minimization) of weld joints, the productivity and the reliability will be improved.

• International Journal of Korean Welding Society
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• v.3 no.1
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• pp.2-7
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• 2003

Laser welding application for car body manufacturing has many advantages in the stiffness and the lightness of vehicle, the productivity of assembly line, and the degree of freedom in design. This presentation will express the innovation of car body manufacturing including parameter optimization, process modeling, and system integration. In this application the investment for systems was cut down dramatically by real time switching over the laser path between two welding stations. Points of technical discussion are as follows; optimization of parameters such as laser power, robot speed and trajectory, compact and useful design of jig & fixture to assure welding quality for 3 sheet-layer zinc-coated steel, system integration between 4㎾ Nd:YAG laser device and the other systems, on-line real time welding quality monitoring system, perfect safety standards for high power laser, minimization of consumption costs such as arc lamp, protective glass for optic, etc. This application was successfully launched mass production line in 2001. The laser-welded line of side panel consists of 122 stitches totally. And the length is about 2.4m.