Multi-objective optimization of gas metal arc welding parameters and sequences for low-carbon steel (Q345D) T-joints

Abstract

Q345D high-quality low-carbon steel has been extensively employed in structures with stringent welding quality requirements. A multi-objective optimization of welding stress and deformation was presented to design reasonable values of gas metal arc welding parameters and sequences of Q345D T-joints. The optimized factors included continuous variables (welding current (I), welding voltage (U) and welding speed (v)) and discrete variables (welding sequence (S) and welding direction (D)). The concepts of the pointer and stack in Visual Basic (VB) and the interpolation method were introduced to optimize the variables. The optimization objectives included the different combinations of the angular distortion and transverse welding stress along the transverse and longitudinal distributions. Based on the design of experiments (DOE) and the polynomial regression (PR) model, the finite element (FE) results of the T-joint were used to establish the mathematical models. The Pareto front and the compromise solutions were obtained by using a multi-objective particle swarm optimization (MOPSO) algorithm. The optimal results were validated by the corresponding results of the FE method, and the error between the FE results and the two-objective results as well as that between the FE results and the three-objective optimization results were less than 17.2% and 21.5%, respectively. The influence and setting regularity of different factors were discussed according to the compromise solutions.