Condition Based Monitoring

Introduction

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.

How It Works

1. Data collection: Sensors measure parameters like vibration, temperature, pressure, or current.

2. Data processing: MES and BDE systems structure and compare this data against thresholds.

3. Anomaly detection: Deviations are identified and classified as potential faults.

4. Automated action: When limits are exceeded, the MES creates a maintenance task or alert.

5. Feedback loop: Maintenance outcomes are recorded for continuous improvement.

Integration with MES, BDE, and OEE

• 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.

Benefits

• 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

Example

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

Conclusion

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.