• Journal of Ocean Engineering and Technology
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• v.17 no.2
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• pp.14-20
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• 2003

In this paper, a practical design criteria for judgement of crack occurrence in weldments is presented as a function of typical welding parameters, such as diffusible hydrogen, restraint intensity, and preheating temperature. The elastic analyses using the finite element techniques are employed in order to quantify the restraint intensities, numerically. Systematic experiments are also conducted in order to investigate the propensity of crack to typical welding parameters. The results of numerical estimation using the proposed method for the experimental specimens show the usefulness as a practical tool in welding induced crack problems with extensive uncertainties. Systematic experiments are also conducted in order to investigate the propensity of crack to typical welding parameters. The results of numerical estimation using the proposed method for the experimental specimens show the usefulness as a practical tool in welding induced crack problems with extensive uncertainties.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.937-942
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• Journal of Welding and Joining
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• v.15 no.3
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• pp.65-78
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• 1997

The effect of $O_2$and Al contents and the variation of welding parameters such as arc currents, welding speed on the weld penetration was investigated. Examination of weld penetration using GTAW was accomplished in the ferritic STS410L and austenitic STS304. Good penetration could be controlled by the variation of $O_2$ and Al contents in STS304. However, influences of $O_2$ and Al contents on the ferritic STS410L are far less than those on the austenitic STS304. Welding parameters should be considered first before controlling $O_2$ and Al contents for a good penetration in ferritic STS410L. In the simulation study under the stationary heat sources, the results of simulation and experiment have a similar tendency.

• Journal of Welding and Joining
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• v.16 no.4
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• pp.63-72
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• 1998

In this study, the effects of the current pulsing conditions, on the spatter generation rate during the $CO_2$ gas metal arc welding (GMAW) were investigated. Normally using the inverter type power supply, of which the welding current waveform was regulated to reduce the spatter generation rate, but in this study pulsing was imposed on the welding current. Observation of the metal transfer phenomena during the pulsed current GMAS indicated that the droplet transfer from the electrode via the short circuit transfer and the repelling transfer mode could be minimized by selecting optimum combinations of pulsing parameters, which include base and peak current, base and pak duration. It was also demonstrated in this study that proper combinations of the pulsing parameters led to reduce generation of spatters during GMAW shielded by $CO_2$ gas.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.89-95
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• 1997

Welding technique is widely applied to general industry such as pressure vessel for chemical plant, pipe system, heavy industry, and automobile. There are some points which must be considered when robot system is used in welding automation process for productivity improvement. Welding quality is governed by heat input, and this quantity can be different according to shape, property, and thick of material . For desired heat input , weld input parameters such as welding voltage, current, and welding velocity must be determined with those consideration. Until now these parameters have been determined mainly by experience of operator. In this study, the size of welding zone was predicted by fuzzy rules were constructed from the relation between welding variables and weld pool size. Inverse model method which welding control input for welder is determined with optimum voltage and current by fuzzy controller is validatied by computer simulation.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.82-88
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• 2002

Simulation systems allow a close inspection of the relation between welding parameters and the resulting weld seam. These systems are very useful in education of weld staff as well as production and planning. In training the influence of variations of parameters can be investigated without the need for real welding experiments. In the design phase requirements of the welding process can be taken into account without several iteration cycles. By estimating a good parameter set for the given welding task the set up phase for a new production cycle can be reduced

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.72-74
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• 2006

The application of the variable polarity plasma arc welding process to A12219 is described. The thickness of aluminum alloy is 11.45mm and 5.08mm. 1-pass keyhole welding is applied to butt welding and 2-pass welding is also applied to thick material. During welding, all welding parameters are controlled by automated system and acquired by 10kHz rate. This paper covers the welding parameters, result of non-destructive test and tensile test.

• Journal of Welding and Joining
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• v.29 no.6
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• pp.82-87
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• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.2
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• pp.209-217
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• 2015

Generally welding is one of the most important processes to have a strong influence on the quality and productivity from a manufacture-based industry such as shipbuilding, automotive and machinery. The GMA(Gas Metal Arc) welding process involves large number of interdependent welding parameters which may affect product quality, productivity and cost effectiveness. To solve such problems, mathematical models are required to select the welding parameters for GMA welding process. In this study, the GMA welding process was studied using the information generated during the welding. The statistical analysis of a generalized regression approach was conducted by the following three methods: Firstly using the mathematical model (linear regression, 2nd regression); Secondly GA(Genetic Algorithm) with intelligent models; And finally using response surface analysis of models to develop the relationships between welding parameters and bead width as welding quality.

• Journal of Welding and Joining
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• v.32 no.1
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• pp.28-33
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• 2014

In this paper, I-butt welding with 6mm thickness using Plasma-GMA welding was carried out. And weld characteristics of the Al-5083 aluminium alloy for Plasma-GMA hybrid welding was evaluated. The orthogonal experimental design was used to investigate the influence of plasma-MIG welding parameters such as plasma current, wire feeding rate, MIG-welding voltage and welding speed on the weld bead geometry and tensile strength using the ANOVA(Analysis of Variation). Then we conducted evaluation of contribution for process parameters. ANOVA results show that bead dimensions are affected by wire feeding speed, welding voltage and welding speed and tensile strength is mainly affected by welding speed and plasma arc current. Tensile strength was decreased by rise in plasma welding current because GMA welding current was decreased by plasma arc.