Prediction of submerged arc weld-metal composition from flux ingredients with the help of statistical design of mixture experiment

A prediction model has been developed for submerged arc weld-metal chemical composition in terms of flux ingredients with the help of statistical experiments for mixture (extreme vertices design). Bead-on-plate weld deposits as per statistical mixture design experiments were performed at the following welding parameters: current (400 A), voltage (26 V), speed (4.65 mm/s) and electrode extension (30 mm) using CaO–MgO–CaF2–Al2O3 flux system. The results show that some of the individual flux ingredients and their binary mixtures have a predominant effect on weld-metal oxygen, manganese, silicon, sulphur, nickel and carbon content. The predicted results show a reasonably good agreement with the experimental results, which were obtained by performing the actual experiments based on a randomly designed flux. Analysis of the experimental data indicate that several mechanisms such as basicity index, oxygen potential, oxide stability, viscosity, electrode chemical reaction, kinetics of slag–metal reaction, etc. are operating simultaneously to yield the final weld-metal composition.