A novel method, independent component analysis ( ICA ), is introduced to gas metal arc welding (GMAW) process monitoring. ICA was applied to arc signals, I. E. Welding current and arc voltage, to remove the correlation between them and extract an independent component IC. Two series of robotic GMA W experiments were carried out to study the feasibility of ICA for online monitoring. It was found that IC put up an abnormity when there was a step disturbance in the welding process.Experimental results showed that the IC could be used as a state variable representing the process variation. By applying statistical process control ( SPC) for the obtained IC, a burning-through defect was isolated from the normal operation. The comparison between ICA and principal component analysis (PCA) was also made for the processes, which led to an interesting result and was in need for further study.