A novel framework for structuring and automating schedule-ready data from BIM for advanced construction scheduling

Construction scheduling still relies on fragmented manual preparation of activity, location, and labor data, even when BIM models are available. This paper addresses the challenge of systematically structuring and automatically extracting enriched BIM data to enable schedule‑ready inputs for advanced construction scheduling. The paper develops an Enhanced Planning and Scheduling (EPS) based framework and applies it through BIM enrichment, spatial decomposition, classification mapping, labor-hour calculation, and Dynamo-based data extraction in a building case. The framework generates a reusable dataset that links model elements to zones, floors, workspaces, activity categories, labor hours, and EPS priority IDs for downstream scheduling. The paper’s contribution lies in providing a structured EPS-based framework that transforms enriched BIM data into reusable schedule-ready inputs linking locations, activity categories, labor hours, and priority logic for downstream scheduling. Further research is needed to validate the framework across various project types and scheduling workflows, and to examine dynamic model–schedule updating and AI-assisted scheduling integration.