During dense hard-soil excavation, the stick sustains large digging resistance, and long-term static and cyclic impact loads frequently cause failure of critical structural components. Balancing structural performance and digging capacity remains a core bottleneck in excavator attachment design. Using a 20-ton hydraulic excavator as the research prototype, this study proposes a Structure-Mechanism Collaborative Optimization (CO) approach that explicitly accounts for the coupling between mechanism parameters and structural performance. A multidisciplinary CO model was constructed, in which stick digging force and equivalent von Mises stress were calculated from experimental data and critical dangerous conditions were identified from stress distributions. Optimal Latin Hypercube Design (OLHD) combined with Kriging surrogate models was employed to build three surrogate models for digging force, maximum equivalent stress, and stick mass, substantially reducing computational cost. The CO model was subsequently solved by intelligent optimization algorithms under practical engineering constraints. Results demonstrate a 9 % increase in theoretical digging force, a 7 % reduction in maximum equivalent stress, and a 9 % decrease in stick weight.