Bim-driven scheduling optimization for in-situ production and yard-stock integration of precast concrete members

The construction industry faces persistent challenges of inefficiency and fragmentation. In precast concrete (PC) projects, in-situ production and yard-stock management require precise coordination of production cycles, storage layouts, and installation schedules, yet existing studies have rarely addressed their integrated optimization. This study proposes a BIM-driven scheduling optimization framework that incorporates probabilistic simulation (Oracle Crystal Ball) into BIM-based 4D modeling. The framework was applied to steel-reinforced precast concrete components in a large-scale logistics project, with the aim of minimizing project duration and improving yard-stock efficiency under site-specific constraints. Simulation results demonstrated a strong positive correlation between lead-time and project duration (+0.58), identifying lead-time control as a critical scheduling variable. A negative correlation between duration and yard-stock area (–0.52) confirmed that timely mold utilization improves spatial efficiency, while crane deployment showed minimal impact. The optimized schedule achieved 6.3 months, reducing the original 8-month plan by 10% and surpassing the client’s contractual timeline by 75%. This research contributes by introducing one of the first BIM-based frameworks that integrates production, storage, and installation into a unified scheduling model, providing both practical decision support and a foundation for future objective optimization.