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An experimental study on optimizing for tandem gas metal arc welding process

Lee J. P., Park M. H., Kim D. H., Jin B. J., Shim J. Y., Kang B. Y., Kim I. S.

Journal of Achievements in Materials and Manufacturing Engineering

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2015

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Vol. 68, nr 2

72--79

EN

Purpose: 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. Design/methodology/approach: 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 develop curve equation for predicting the optimized process parameters and quality characteristics by analysing the S/N ratio. Findings: 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. Research limitations/implications: 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. Originality/value: This paper focused on the anode-cathode distance that can prevent arc blow in tandem GMA welding process. We also analysed the welding quality characteristics according to the bead geometry and welding parameters through S/N ratio dependent on the welding speed and flow rate variation of shielding gas. Finally, a mathematical model being able to predict the welding quality based on the given welding parameters using statistical method has been developed.

2

A experiment study for welding optimization of fillet welded structure

Na H. H., Kim I. S., Kang B. Y., Shim J. Y.

Journal of Achievements in Materials and Manufacturing Engineering

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2011

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Vol. 45, nr 2

178--187

EN

Purpose: This study aims to examine the interaction between process parameters and bead geometry, to perform the research to predict optimal bead geometry (bead width, reinforcement height, left leg length, right leg length) through the analysis of experimental data. For this, not only linear and the curvilinear equations were developed to predict bead geometry, but also interactions between process parameters and bead geometry were analysed through sensitivity analysis. Design/methodology/approach: A Taguchi method was applied for the optimization of process parameters, as well as bead geometry was predicted using a Neural Networks (LM) learning algorithm. Findings: The data generated through experimental studies conducted in this study has employed to validate its effectiveness for the optimization of bead geometry on process parameters (welding current, welding voltage, welding speed), and to present the criteria to control the process parameters to achieve a good bead geometry. Research limitations/implications: By applying Taguchi method, process parameters (welding current, welding voltage, welding speed) and bead geometry (bead width, reinforcement height, leg length) were analysed. Originality/value: This study has developed mathematical models and algorithms to predict or control the bead geometry in GMA fillet welding process, and analysed the S/N ratio to which Taguchi theory was applied for sensibly to the process parameters.

3

Control of welding process for BV-AH 32 steel

Kim H. H., Kim I. S., Kim I. J., Kang B. Y.

Archives of Materials Science and Engineering

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2008

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Vol. 33, nr 1

45-48

EN

Purpose: The GMA welding process involves large number of interdependent variables, which may affect product quality, productivity and cost effectiveness. With the combination of sensors and mathematical models, increased effectiveness in control of the automatic welding process was achieved. In this study, it focuses on development of mathematical models for the selection of process parameters using BV-AH32 steel for shipbuilding industry. Design/methodology/approach: The base material used for this study was the BV-AH32 steel with 12 mm in thickness for multi-pass butt welding. A curvilinear regression analysis was performed with the predictors that were found to be statistically significant against bead geometry based on the results from the above factorial design. The adequacy of the models and the significance of coefficients were tested by applying the analysis of variance technique and T-test respectively. Findings: From the above resultant equation for estimation of bead geometry, the sensitivity equations are obtained by differentiation with respect to process parameters of interest such as arc current, welding voltage and welding speed that are explored. Practical implications: Sensitivity analysis has been investigated to represent the effectiveness of the processing parameters on these empirical equations and showed that the change of process parameters affects the bead width and bead height more strongly than penetration relatively. Originality/value: These models are extended to shielding gas composition, weld joint position, polarity and many other parameters which are not included in this research in order to establish a closed loop feedback control system to minimize possible errors from uncontrolled variations.