The proposed framework reduces cost overruns and improves predictive maintenance in construction using digital twins and building information modeling.
The management of large-scale architectural engineering projects (e.g., airports, hospitals) is plagued by information silos, cost overruns, and scheduling delays. While building information modeling (BIM) has improved 3D design coordination, its static nature limits its utility in real-time construction management and operational phases. This paper proposes a novel synergistic framework that integrates the static, deep data of BIM with the dynamic, real-time capabilities of digital twin (DT) technology. The framework establishes a closed-loop data flow from design (BIM) to construction (IoT, drones, BIM 360) to operation (DT platform). We detail the technological stack required, including IoT sensors, cloud computing, and AI-driven analytics. The application of this framework is illustrated through a simulated case study of a mega-terminal airport construction project, demonstrating potential reductions in rework by 15%, improvement in labor productivity by 10%, and enhanced predictive maintenance capabilities. This research contributes to the field of construction engineering by providing a practical model for achieving full lifecycle digitalization and intelligent project management.
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Longyan Tian (2025) studied this question.
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