Condition Based Monitoring (CBM) is a maintenance approach that continuously monitors machine conditions to detect wear, anomalies, or failures early. Instead of performing maintenance at fixed intervals, actions are triggered only when data indicates a real need.
CBM is a cornerstone of Predictive Maintenance and a key driver of OEE improvement. With MES, BDE, and IoT integration, manufacturers can collect and analyze live data to enable real-time, condition-driven maintenance.
Data collection: Sensors measure parameters like vibration, temperature, pressure, or current.
Data processing: MES and BDE systems structure and compare this data against thresholds.
Anomaly detection: Deviations are identified and classified as potential faults.
Automated action: When limits are exceeded, the MES creates a maintenance task or alert.
Feedback loop: Maintenance outcomes are recorded for continuous improvement.
MES contextualizes sensor data with production information (machine, order, shift).
BDE provides runtime and downtime data for correlation with anomalies.
OEE analytics quantify the impact of maintenance on availability and performance.
Together, these systems turn CBM from passive monitoring into an active optimization process.
Reduced downtime through early fault detection
Lower maintenance costs with targeted interventions
Improved OEE and equipment reliability
Data-driven transparency across maintenance processes
Extended machine lifetime through predictive action
A precision parts manufacturer implemented vibration-based CBM in its cloud MES. The system automatically triggered maintenance when thresholds were exceeded. Within a year:
30 % fewer breakdowns
20 % lower maintenance costs
8-point OEE improvement
Condition Based Monitoring enables predictive, efficient, and transparent maintenance. By combining MES, BDE, OEE, and IoT sensor data, manufacturers gain real-time insight into machine health and ensure maximum uptime with minimal intervention — a core element of the Smart Factory.