• Journal of Welding and Joining
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• 제15권3호
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• pp.88-98
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• 1997

Welding defects, such as porosity and spike, have sometimes occurred in deep penetration electron beam welds. These defects are known to be one of the serious problem in electron beam welds. So, effects of active parameters ($a_b$) on bead shape and occurrence of defects in electron beam welds of heavy section 9%Ni steel plates were investigated. Partial penetration welding in flat position, and deep penetration welding of 10 ~ 28mm depth were investigated in this study. It is desirable to select low accelerating voltage and above the surface focus position $a_b$$\geq$1.2 at which a wine-cup shaped bead is obtained to avoid the welding defects such as spike and root porosity. When the accelerating voltage of electron beam was low (90kV), active parameter ($a_b$) did not influence on the bead width, penetration depth and weld defects significantly. However, in case of high voltage ($\geq$120kV), active parameter ($a_b$) was sensitively associated with penetraton depth and weld defects, i.e. when the active parameter (($a_b$) was in the range of 0.6 to 1.0, the depth of penetration was always over the target (23mm), while the depth of penetration was dramatically decreased with further increase of active parameter ($a_b$). The weld defects were decreased with the increase of active parameter $a_b$ resulting in the decrease of energy density of the focused beam in the root part of fusion zone.

• 한국공작기계학회논문집
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• 제15권5호
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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 Welding and Joining
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• 제33권2호
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• pp.91-96
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• 2015

The laser-arc hybrid welding of SS400 steel was carried out with the use of disk laser equipment of 6.6kW maximum power and MAG equipment of pulse mode. Parameter regarding heat input is one of the most important factors that directly affect penetration characteristics and welding defect. Therefore in this study, the effects of laser power, welding speed and current, voltage and pulse correction were investigated. As experiment result, it was found that the lower heat input, the more likely humping bead is formed at the back, and such humping bead could be suppressed by increasing laser power and arc current or decreasing welding speed, thus increasing heat input. Also deep penetration could be achieved by reducing arc voltage or pulse correction parameter in the same welding condition.

• Journal of Welding and Joining
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• 제33권4호
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• pp.17-23
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• 2015

Laser-gas metal arc hybrid welding has been considered as an alternative process of gas metal arc welding for offshore pipe laying. Fiber delivered high power lasers which enable deep penetration welding were recently developed but high power welding characteristics were not fully understood yet. In this study, the influence of shielding gas composition on welding phenomena in high power laser welding was investigated. Bead shapes, melt ejection and dropping were observed after autogenous laser welding with 100% Ar, Ar-20% $CO_2$, Ar-50% $CO_2$, and 100% $CO_2$ shielding gas. Process parameter window was widest with Ar-50% $CO_2$ shielding gas and the penetration was deepest with 100% $CO_2$ shielding gas. The melt dropping was not observed when Ar-50% $CO_2$ or 100% $CO_2$ shielding gas was supplied.

• Journal of Welding and Joining
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• 제20권2호
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• pp.102-108
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• 2002

Resistance spot welding of aluminum alloys is based upon Joule heating of the components by passing a large current in a short duration. Since aluminum alloys have the potential to replace steels fur automobile body assemblies, it is important to study the process robustness of aluminum spot welding process. In order to evaluate the effects of process parameters on the weld quality, major process variables and abnormal process conditions were selected and analyzed. A newly developed two-stage, sliding-level experiment was adopted fur effective parameter design and analysis. Suitable ranges of welding current and button diameters were obtained through the experiment. The effects of the factors and their levels on the variation of acceptable welding current were considered in terms of main effects. From the results, it is concluded that any abnormal process condition decreases the suitable current range in the weld lobe curve. Pareto analysis of variance was also introduced to estimate the significant factors on the signal-to-noise (S/N) ratio. Among the six factors studied, fit-up condition is found to be the most significant factor influencing the SM ratio. Using a Pareto diagram, the optimal condition is determined and the SM ratio is significantly improved using the optimal condition.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 추계학술대회 논문요약집
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• pp.150-150
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• 2003

• Journal of Welding and Joining
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• 제11권4호
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• pp.44-56
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• 1993

The arc welding processes are substantially nonlinear, in addition to being highly coupled multivariable systems, Frequently, not all the variables affecting the welding quality are known, nor may they be easily quantified. From this point of view, decoupling between the welding parameters from the welding quality is very difficult, which makes it also difficult to control the welding parameters for obtaining the desired welding quality. In this study, a neural network based on the backpropagation algorithm was implemented and adopted for the selection of gas metal arc welding parameters of the fillet joint, that is, welding current, arc voltage and welding speed. The performance of the neural network for modeling the relationship between the welding quality and welding parameters was presented and evaluated by using the actual welding data. To obtain the optimal neural network structure, various types of the neural network structures were tested with the experimental data. It was revealed that the neural network can be effectively adopted to select the appropriate gas metal arc welding parameter of fillet joints for a given weld quality.

• International Journal of Korean Welding Society
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• 제1권1호
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• pp.17-22
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• 2001

Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.

• International Journal of Korean Welding Society
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• 제3권1호
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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.

• Journal of Welding and Joining
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• 제17권4호
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• pp.69-75
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• 1999

Spot welding has been used in the sheet metal joining processes because of its high productivity and convenience. In this study, predicting methods of fatigue life of spot welded joint have been investigated and fatigue and static tests were conducted with the peel-tension specimens using cold rolled steel plate(SPCC). Fatigue life of peel-tension spot welded joint was influenced by tail effect. Fatigue life evaluation using modified stress index parameter, considering the effective eccentric length, can predict the life more exactly than conventional stress index parameter.