• 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.

• Proceedings of the KWS Conference
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• 2005.06a
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• pp.82-84
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• 2005

Among the advanced welding processes which are superior to conventional process, Electron beam welding and Narrow-gap TIG welding are most prospective in being applicable for the heavy industry field. With STS316LN, which is high strengthened austenitic stainless steel, the characteristic evaluation for these welding processes was carried out through the mechnical tests and property analyses. For the tensile strength EBW is better while in reverse for the yield strength. In Narrow-gap TIG the distribution of hardness values has some deviation according to the thickness direction while EBW has a tendency of a litter high hardness values in weld metal. After EB welding brings the reduction of nitrogen content, in TIG welding weld metal depends on the contents of welding material. Both processes have almost austenitic structure, but weld metal of EBW is also shown terrific structure

• Journal of Welding and Joining
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• v.32 no.2
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• pp.43-47
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• 2014

Famous artificial neural network (ANN) is applied to predict proper process window of arc welding. Target weldment is variously combined lap joint fillet welding of automotive steel plates. ANN's system variable such as number of hidden layers, perceptrons and transfer function are carefully selected through case by case test. Input variables are welding condition and steel plate combination, for example, welding machine type, shield gas composition, current, speed and strength, thickness of base material. The number of each input variable referred in welding experiment is counted and provided to make it possible to presume the qualitative precision and limit of prediction. One of experimental process windows is excluded for predictability estimation and the rest are applied for neural network training. As expected from basic ANN theory, experimental condition composed of frequently referred input variables showed relatively more precise prediction while rarely referred set showed poorer result. As conclusion, application of ANN to arc welding process window derivation showed comparatively practical feasibility while it still needs more training for higher precision.

• Journal of Welding and Joining
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• v.32 no.2
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• pp.70-75
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• 2014

In automotive industry, applying of Mg alloy to autobody has been issued recently as a light metal. But poor resistance spot weldability of Mg alloy is blocking commercialization. So studies on improving resistance spot weldability of Mg alloy is increasing continuously. For reduce loss of heat input during welding, inverter DC power source is considered because of short rise time to target welding current. But rapid rising of welding current can increase temperature rapidly in nugget and oxide film between electrode and base metal, and that causes generating expulsion on low welding current range. In this study, for increase optimum welding current range and prevent generating expulsion, applicate various types of welding current waveform controls during resistance spot welding. For analysis effects of each current waveform control, acceptable welding current regions according to electrode force and welding time is determined and lobe diagram is derived. In result, pre heat is proposed as optimum type of welding current waveform control.

• Fashion & Textile Research Journal
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• v.15 no.3
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• pp.452-460
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• 2013

This study conducted a performance evaluation of protective clothing materials used for welding in a hazardous shipbuilding industry work environment. The welding process was selected as the one that most requires industrial protective clothing according to work environment characteristics. Flame proofing and convection heat protection performance (HTI) in the heat transfer characteristics of protective clothing material were indicated in the order of SW1(Oxidant carbon)>SW2(silica coated Oxidant carbon)>SW4(Oxidant carbon/p-aramid)>SW3(flame proofing cotton). However, radiant heat protection performance (RHTI) and the heat transfer factor (TF) were indicated in the order of SW1>SW4>SW2>SW3 and showed different patterns from the convection heat protection performance. SW1 showed superior air permeability and water vapor permeability. The tensile strength and tear strength of welding protective clothing material were indicated in the order of SW4>SW2>SW3>SW1 and showed that a blend fabric of p-aramid was the most superior for the mechanical properties of SW4. SW1 had excellent heat transfer properties in yet met the minimum performance requirements of tensile strength proved to be inappropriate as being a material for welding protective clothing. The abrasion resistance of woven fabric proved superior compared to nonwoven fabric; however, seam strength and dimensional change both met the minimum performance requirements and indicated that all samples appeared non-hazardous. Finally, oxidant carbon/p-aramid blend fabric appeared appropriate as a protective clothing materials for welding.

• Journal of Welding and Joining
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• v.20 no.3
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• pp.46-53
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• 2002

The expolitation of substitute material and new manufacturing technology of the automobile body panel for next generation cars have been steadily professed by advanced automobile companies. High strength steel of TRIP (Transformation of Induced Plasticity) type is developed in response to demands about crash safety and high strength of automobile. In this study, basic technologies can fix up problems occurring on the mass production and applied to the other forming methods will be prepared through rasping a property of TRIP material.

• Journal of Welding and Joining
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• v.30 no.2
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• pp.5-10
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• 2012

• Transactions of Materials Processing
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• v.19 no.8
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• pp.452-459
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• 2010

It was investigated that two plates of aluminum can be welded by hot extru-shear welding process with extru-shear welding dies, and that the welding strength and metal flow on the welding section were analyzed by computer simulation according to the welding variables such as inclined angle of cutter and overlapped length of plates and temperature of plates. It was known by computer simulation that welding strength on the welding section of plates could be influenced by the inclined angle of cutter and overlapped length of plates and temperature of plates. And it was known by experiments that two plates of aluminum can be welded on the end sections by hot extru-shear welding process using extru-shear welding dies, and that welding strength is the highest when inclined angle of dies is $70^{\circ}$, and overlapped length is 1.2 mm, and temperature is $520^{\circ}$, when aluminum 5052 two plates with 1.6 mm thickness are used as welding material.

• Journal of Welding and Joining
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• v.15 no.5
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• pp.74-83
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• 1997

Effect of welding parameters such as current, speed and electrode pressure on the weld quality of tin coated steels for small containers was discussed in this paper. Welding was performed with low frequency wire seam welding system which was loaded with 1.5mm in diameter copper wire electrode. The welding parameters were monitored at the position close to the welding spot so as to minimize the instrumentation error, and the signals were stored into a digital data acquisition system before analysis. Results showed that critical current for sufficient nugget size increased as the base material thickness increased, while the width of the optimum welding range was reduced. The acceptable welding condition derived from this study was found to be effective within the thickness range of $\pm$10% of the nominal (0.25mm) thickness. Tin coating layer was proved not to affect seriously on the weld quality, i.e. strength and formability, since consumable wire electrode was used in this process. Test results also demonstrated that the welding current was thought to be the most effective parameter to form an acceptable weld, while welding speed or electrode pressure exerted less effect on the nugget formation. However, these two parameters played an important role because the former was related to the nugget overlap interval, and the latter, to the formation of expulsion during welding.

• International Journal of Korean Welding Society
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• v.1 no.1
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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.