Optimization of GMAW process parameters from clustered bead geometry based on the Fuzzy C-Means algorithm

Abstract

The increasing demand for cost savings on structural and industrial materials with weld joints possessing higher strength value has brought to the fore, the importance of optimizing Gas Metal Arc Welding(GMAW) process parameters. This article examines the possibility of optimizing the process parameters of GMAW based on a fuzzy clustering approach. A Fuzzy C-Means algorithm was used to cluster the bead geometry obtained from the GMAW process. The chosen process parameters were then optimized from the clustered bead geometry. The study concludes that the use of the Fuzzy C-Means clustering technique has improved the existing process parameters, giving users a more efficient welding process.