Optimization of Welding Sequence for Frame Structures Based on Discrete Particle Swarm Optimization to Mitigate Welding Deformation

Welding deformation in large thick-plate structures can severely compromise manufacturing quality, making its prediction and control a critical engineering challenge. This study focuses on an engineering vehicle frame, for which a finite element model was developed to investigate the effects of welding sequence and direction on residual deformation, using a local-global strain mapping approach. Thermo-elasto-plastic simulations were first performed on T-joints and fillet joints to extract local plastic strains, which were subsequently mapped onto the global elastic model to compute overall structural deformation. The simulation results showed good agreement with experimental measurements, with a deviation of approximately 5.6%, confirming the reliability of the proposed method for predicting welding-induced deformation and stress in complex assemblies. To further optimize the welding strategy, a surrogate model was constructed based on Design of Experiments (DOE), and a Discrete Particle Swarm Optimization (DPSO) algorithm was employed. The optimized welding sequence and direction reduced the maximum deformation by 43%, while significantly lowering computational cost without sacrificing accuracy. This integrated approach offers valuable guidance for welding process design in engineering vehicle frames and other large welded structures.