Statistical modelling and optimization of clad characteristics in SAW welding of SS-304

Abstract

Submerged arc welding (SAW) is a type of welding process having wide range of applications like in fabrication of pressure vessel, pipe line, off shore structures, oil industry, etc., because of its high melting efficiency, high production rate and automation. Weld input factors such as welding voltage, welding current, travel speed, nozzle to plate distance and electrode diameter have a significant impact on the standard of created weld bead. Response surface methodology is used in the present work to find out the influence of welding voltage, welding current and travel speed on weld bead geometry. Face centred central composite design technique of RSM is used for Design of Experiment. It has been discovered that weld bead width grows with higher welding voltage but there is decrease in weld bead height, with increase in welding current there is increase in both weld bead width and weld bead height also but when travel speed is increased there is decrease in both weld bead width and weld bead height. The genetic algorithm for minimization of both weld bead width and height is also done. The predicted results from the created mathematical model, optimized model and the related experimental result are in good agreement.