A BIM based Decision Support System Framework for Predictive Maintenance Management of Building Facilities
Facility management (FM) involves multidisciplinary efforts and requires the coordination of different people, properties and processes. Therefore, extensive information of multiple dimensions needs to be stored and managed for FM. Currently, some buildings and facilities are managed manually, while some use databases and automated devices like sensors to capture and manage FM records. However, the current approaches do not fully utilize the collected FM records and provide a user friendly interface for facilitating the operation and maintenance (O&M) of building facilities. Several academic and commercial efforts attempted to leverage building information modeling (BIM) technology to link and visualize FM records, but these efforts are still weak in proactively predicting asset failure, suggesting maintenance schedules and allocating budget for FM. This paper presents a decision support system framework based on BIM for O&M of buildings. The framework consists of three modules: Condition Assessment Module, Failure Prediction Module, and Maintenance Planning and Budget Allocation Module. The Condition Assessment Module manages the facility condition data that are automatically captured by sensor devices as well as collected via inspection and condition survey. Incorporated with failure records and lifetime estimation models, the Failure Prediction Module integrates with the Condition Assessment Module and forecasts component failures. The results provide a basis for predictive maintenance of building facilities. BIM is also leveraged to manage and visualize not only the FM data but also the predictive maintenance results. Since each O&M action has its cost implications, the Maintenance Planning and Budget Allocation Module is included in this proposed framework to help facility managers evaluate cost implications and dynamically adjust maintenance plan.