Purpose This study develops an integrated building information modeling (BIM)-based model for predictive maintenance management in educational buildings by combining building condition assessment (CA) and deterioration prediction (DP) using a Markov chain model. Design/methodology/approach The methodology involves categorizing building assets into a hierarchy, calculating relative weights (RW) for components and optimizing maintenance schedules and resource allocation. The integration of the BIM model with facility management (FM) software enhances data exchange and decision-making, providing facility managers with graphical representations of data and a platform for managing both preventive and corrective maintenance. Findings The effectiveness of the model was validated using data from a real educational facility, which demonstrated improvements in maintenance, and cost reduction. Specifically, the model supports proactive maintenance scheduling, and task prioritization, leading to reduction in maintenance costs and enhancing the efficiency of maintenance operations. Through a real-world case study, the model achieves 22% maintenance cost reduction, and 89% prediction accuracy, demonstrating its practical advantages over reactive. Originality/value This approach not only extends the lifecycle of building assets but also improves overall asset management practices in educational facilities, offering original insights into the integration of CA and DP within a BIM framework. This innovative model serves as a scalable solution for efficient data-driven FM that is potentially adaptable to other types of buildings. Furthermore, the model bridges the gap between advanced research and practice by introducing a simplified approach. This paper introduces a novel BIM-based framework that unifies (CA), and (DP) into a single predictive maintenance model tailored for educational buildings.
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Nageeb et al. (2026) studied this question.
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