Construction projects worldwide lose an estimated 20–30% of planned schedule time to delays that were detectable but undetected before they became critical. The gap is not in sensing technology. The gap is in schedule intelligence. The most advanced work in construction digital twins including Bhadaniya and Gheisari (2026) in Advanced Engineering Informatics establishes sophisticated frameworks for UAS-driven, 4D BIM-synchronized physical progress monitoring. These frameworks depend on a project schedule as input. That schedule must be current, structured, and synchronized with the digital model. The paper's own Step 1 describes this update as a manual process. This is the gap this research addresses: the scheduling side of construction digital twins remains human-dependent, unstructured, and disconnected from the real-time project control data that planning engineers produce every day in Primavera P6. Doukari et al. (2022, Buildings) state directly that automatic generation of 4D BIM from construction schedules is "not currently possible, and the process requires considerable manual effort." Tan and Matta (2024, IISE Transactions) formalize the digital twin synchronization problem as an optimal control challenge — but their framework applies to manufacturing uptime states, not to CPM schedule logic. Limited published work applies synchronization optimization to the activity-network structure of a Primavera P6 construction schedule.