• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.22-28
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• 2013

Robotic GMA (Gas Metal Arc) welding process is one of widely acceptable metal joining process. The heat and mass inputs are coupled and transferred by the weld arc to the molten weld pool and by the molten metal that is being transferred to the weld pool. The amount and distribution of the input energy are basically controlled by the obvious and careful choices of welding process parameters in order to accomplish the optimal bead geometry and the desired quality of the weldment. To make effective use of automated and robotic GMA welding, it is imperative to predict online faults for bead geometry and welding quality with respect to welding parameters, applicable to all welding positions and covering a wide range of material thickness. MD (Mahalanobis Distance) technique was employed for investigating and modeling the GMA welding process and significance test techniques were applied for the interpretation of the experimental data. To successfully accomplish this objective, two sets of experiment were performed with different welding parameters; the welded samples from SM 490A steel flats. First, a set of weldments without any faults were generated in a number of repeated sessions in order to be used as references. The experimental results of current and voltage waveforms were used to predict the magnitude of bead geometry and welding quality, and to establish the relationships between weld process parameters and online welding faults. Statistical models developed from experimental results which can be used to quantify the welding quality with respect to process parameters in order to achieve the desired bead geometry based on weld quality criteria.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.1939-1946
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• 2012

High performance steel for bridges requires higher performance in tensile and yield strength, toughness, weldability, etc. The purpose of this study is to investigate the weldability of HSB 600 steel. The effects of heat input (1.4~3.2kJ/mm) and postweld heat treatment (PWHT, $600^{\circ}C$, 40hr.) on the TMCP HSB600 steel weldments made by GMAW process were investigated. The tensile strength and hardness of as-welded specimens decreased with increasing heat input. Charpy V-notch impact energy did not show any significant difference by postweld heat treatment. The fine-grained acicular ferrite was mainly formed in the 2.1kJ/mm of heat input while polygonal and side plate ferrites were dominated in the high inputs. Meanwhile, tensile strength and hardness of PWHT weldments decreased due to the coarsening and globularization of ferrite microstructure and reduction of residual stresses with increasing heat inputs. However, there was no significant difference in the impact energy absorption.