Optimization of the welding process parameters of Mg–5Gd–3Y magnesium alloy plates with a hybrid Kriging and particle swarm optimization algorithm

Selecting suitable welding process parameters to obtain optimal mechanical properties of the weld bead in AC gas tungsten arc welding is of vital importance. This paper presents a combination method of the Kriging model and particle swarm optimization for optimizing welding process parameters to achieve the optimum mechanical properties, such as the tensile strength and micro-hardness, of the weld bead in AC gas tungsten arc welding of GW53 magnesium alloy plates. The Taguchi orthogonal array is first employed to construct a database including the input process parameters (welding speed, welding current, and protection gas flow) and the responses (the tensile strength and micro-hardness of the weld joint). Then, the Kriging model is used to establish the relationships between the input process parameters and the responses. The optimal mechanical properties of the weld bead corresponding to the welding process parameters are obtained by the proposed hybrid Kriging and particle swarm optimization algorithm. Finally, the effectiveness of the proposed method is verified by contrasting the mechanical properties, such as the tensile strength and the average micro-hardness, in the welding base metal and the weld bead. Furthermore, the main reasons for the decrease in the mechanical properties of welded plates are described in this paper