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Enhancing facility maintenance using knowledge-based BIM systems
A Ehab1, Mazkour A Mahdi2, Arafa El-Helloty2
1Civil Engineering Department, Badr University in Cairo (BUC), Cairo, 11829, Egypt. Ahmed-Ehab@buc.edu.eg.
Scientific Reports
|December 8, 2025
Summary
This study introduces a simple, Python-based Building Information Modeling (BIM) plugin to optimize building maintenance. The system uses real-time data and predictive models to improve facility management, reduce costs, and extend asset lifespan.
Area of Science:
- Construction Management
- Facility Management
- Software Engineering
Background:
- Traditional building maintenance and facility management methods are complex and inefficient.
- Building Information Modeling (BIM) offers digital solutions but often requires specialized expertise.
- Existing BIM plugins for maintenance can be complicated and demand extensive training.
Purpose of the Study:
- To propose a user-friendly decision support system (DSS) framework plugin for facility management.
- To simplify the planning, tracking, and allocation of maintenance budgets.
- To overcome challenges in current maintenance processes through technological integration.
Main Methods:
- Development of a Python-based framework plugin integrated with BIM.
- Utilizing real-time data and predictive models for maintenance optimization.
- Creating maintenance schedules based on facility condition, equipment type, and usage frequency.
Main Results:
- Reduced building asset downtime and minimized operational costs.
- Extended lifespan of building assets through optimized maintenance.
- Generated reports on resource utilization and expenditure for informed budget planning.
Conclusions:
- The proposed framework plugin offers an innovative and scalable solution for facility management.
- It enhances the efficiency of maintenance planning, scheduling, and resource allocation.
- The system provides a simplified yet effective approach to facility maintenance optimization.
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