• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.70-75
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• 1999

Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor the information about weld characteristics and process paramters as well as modification of those parameters to hold weld quality within the acceptable limits. Typical characteristics are the bead geometry composition micrrostructure appearance and process parameters which govern the quality of the final weld. The main objectives of this paper are to realize the mapping characteristicso f penetration through the learning. After learning the neural network can predict the pene-traition desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) were chosen from an error analysis. partial-penetration single-pass bead-on-plate welds were fabricated in 12mm mild steel plates in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the penetration with reasonable accuracy and gurarantee the uniform weld quality.

• Journal of Welding and Joining
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• v.30 no.2
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• pp.59-64
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• 2012

Welding is an essential process in the automotive industry. Most welding processes that are used for auto body are spot welding and $CO_2$ welding are used in a small part. In production field, $CO_2$ welding process is decreased and spot welding process is increased due to welding quality is poor and defects are occurred in $CO_2$ welding process frequently. But $CO_2$ welding process should be used at robot interference parts and closed parts where spot welding couldn't. Because of the 0.65mm ~ 2.0mm thickness steel sheet were used in the automotive industry, poor quality of welding area such as burn through and under fill were happened frequently in $CO_2$ process. In this paper, we will study about the penetration depth which gives a huge impact on burn through changing a degree of base metal, welding position and torch angle. Voltage, current and welding speed were fixed but degree of base metal, welding position and torch angle were changed. And Cold- Rolled(CR) steel sheet was used. Penetration depth was analysed by multiple regression analysis to derive approximate calculations. And reliability of approximate calculations were confirmed through additional experiments. As the results of this research, we confirmed the effect of torch and plate angle to bead shape. And we present a possibility that can simulate more accurate to weld geometry, as deduced the verification equations that has tolerance of less than 21.69%.