Condition-based monitoring (CBM) is a foundational element of intelligent facility operations. Unlike traditional time-based maintenance, CBM relies on real-time equipment health data to determine when maintenance is actually required.
Facilities contain numerous assets that operate under varying conditions. Fixed maintenance schedules do not account for workload differences, environmental stress, or usage patterns. CBM solves this by continuously assessing equipment condition.
IoT sensors capture operational parameters such as temperature, vibration, acoustic signals, and pressure. AI systems analyze these signals to detect anomalies and performance degradation. Maintenance decisions are triggered by actual equipment health rather than arbitrary timelines.
This approach prevents premature part replacement and reduces unexpected failures. It is particularly valuable for HVAC systems, motors, pumps, and electrical equipment where performance trends reveal early warning signs.
CBM improves reliability, reduces costs, and increases asset utilization. It also feeds predictive models, enabling facilities to move toward fully AI-driven maintenance ecosystems.
