• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.1
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• pp.30-35
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• 2016

Tandem arc welding is a guarantor for high efficiency and cost saving since the quantity of wire which is deposited in the welding is approximated 30% greater that in conventional welding. The welding process is now being successfully applied in many industries. However, in the case of tandem arc welding, good quality and high productivity should depend on the welding parameters. Therefore, an intelligent algorithms for the automatic tandem arc welding process has been necessarily required. In this study, a predictive model based on the neural network by using the data acquired during tandem gas metal arc (GMA) welding process has been developed. To verify the reliability of the developed predictive model, a mutual comparison with the surface of the top-bead width obtained from actual experiments has been analyzed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.199-200
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• 2012

• Journal of Welding and Joining
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• v.32 no.6
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• pp.8-13
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• 2014

One of the main challenges of the automatic arc welding process which has been widely used in various constructions such as steel structures, bridges, autos, motorcycles, construction machinery, ships, offshore structures, pressure vessels, and pipelines is to create specific welding knowledge and techniques with high quality and productivity of the production-based industry. Commercially available automated arc welding systems use simple control techniques that focus on linear system models with a small subset of the larger set of welding parameters, thereby limiting the number of applications that can be automated. However, the correlations of welding parameters and bead geometry as welding quality have mostly been linked by a trial and error method to adjust the welding parameters. In addition, the systematic correlation between these parameters have not been identified yet. To solve such problems, a new or modified models to determine the welding parameters for tandem GMA (Gas Metal Arc) welding process is required. In this study, A new predictive model called STACO model, has been proposed. Based on the experimental results, STACO model was developed with the help of a standard statistical package program, MINITAB software and MATLAB software. Cross-comparative analysis has been applied to verify the reliability of the developed model.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.11
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• pp.1007-1013
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• 2014

In this study to improve the productivity, advantage Tandem circumferential weld process of seam tracking system was applied for the laser vision sensor. Weld geometry scanning laser vision sensor and PLC control unit are used to scan correct positioning of welding torch when the program is implemented so that it can correctly track the welding line. The welding experiment was conducted to evaluate the performance of laser vision seam tracking sensor in tandem welding process. The seam tracking several experiments was to determine the reliability of the system, welding experiments relatively good quality welding bead was confirmed. Furthermore, the PLC program for seam tracking was used to confirm the validity of the application of tandem welding process according to the benefits of increased productivity, which is expected to contribute to national competitiveness.

• Journal of Welding and Joining
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• v.30 no.6
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• pp.49-55
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• 2012

The tandem welding process is one of the most efficient welding processes widely used in material joining technique such as manufacturing of strong and durable structures. It facilitates high rate of joint filling with little increase in the overall rate of heat input due to the simultaneous deposition from two electrode wires. The two electrodes in tandem welding process helps in high-efficiency and high productive of welding process. In this study a automated tandem welding system is developed to determine the correlation between cathode and anode and compared with current ratio of the two electrode torch. Three different inter-electrode distances were chosen, 25mm, 35mm and 45mm to perform the experiment with three different current ratio. From the experiment results, the current ratio between two torch has a large impact on width, height and depth of penetration. In addition, a stable bead geometry is obtained when inter-electrode distance is 35mm.

• Journal of Welding and Joining
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• v.32 no.2
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• pp.22-28
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• 2014

To enhance productivity and provide high quality production material in a GMA welding process, weld quality, productivity and cost reduction affects the number of process variables. In addition, a reliable welding process and conditions must be implemented to reduce weld structure failure. In various industries the welding process mathematical model is not fully formulated for the process parameter and on the welding conditions, therefore only partial variables can be predicted. The research investigates the interaction between the welding parameters (welding speed, distance between electrodes, and flow rate of shielding gas) and bead geometry for predicting the weld bead geometry (bead width, bead height). Taguchi techniques are applied to bead shape to develope curve equation for predicting the optimized process parameters and quality characteristics by analyzing the S/N ratio. The experimental results and measured error is within the range of 10% presenting satisfactory accuracy. The curve equation was developed in such a way that you can predict the bead geometry of constructed machinery that can be used for making tandem welding process.