In precision equipment assembly, the quality of bolted joints is crucial for structural performance and geometric accuracy, yet it often relies on error-prone manual adjustment. This study proposes a deformation-aware optimization method for the multi-bolt pretightening process to simultaneously control accuracy and ensure stiffness. A geometric accuracy prediction model is established to link the dynamically changing bolt preloads (due to elastic interactions) with structural deformation. Concurrently, a layout-independent pretightening sequence constraint model (PSCM) is formulated to generate feasible tightening sequences that guarantee sufficient interfacial contact. These two models are integrated within a hybrid Particle Swarm Optimization-Genetic Algorithm (PSO-GA) framework to optimize the tightening sequence and force distribution. Experimental validation on a large CNC machine bed assembly shows that the proposed method directly achieves the required guideway levelness and reduces straightness and pitch errors by up to 60% and 40%, respectively, compared to the conventional process, demonstrating its effectiveness for precision assembly.
Gan et al. (Wed,) studied this question.