Condition Based Maintenance
Condition-Based Maintenance (CBM) is a proactive maintenance strategy where tasks are triggered by the actual measured condition of an asset, such as vibration, temperature, or oil quality, rather than fixed time intervals or run-to-failure assumptions. It detects physical evidence of warning signs to intervene before failure occurs, functioning as a form of preventive maintenance.
On the shop floor, CBM relies on sensors and monitoring equipment to collect real-time data on parameters like bearing temperature or vibration amplitude. A work order is automatically raised only when a monitored parameter crosses a defined threshold, ensuring maintenance is performed exactly when the asset shows it needs it. In CMMS environments like ServiceGrid, this data is analyzed via algorithms or AI to identify anomalies and trigger maintenance actions, optimizing maintenance schedules and reducing downtime.
How does CBM differ from Predictive Maintenance (PdM)?
CBM is often considered a subset of PdM; while CBM triggers action when a parameter exceeds a limit, PdM (specifically prognostic CBM) uses historical data and machine learning to forecast the exact time of failure (Remaining Useful Life estimation).
What is the relationship between CBM and Reliability-Centered Maintenance (RCM)?
CBM is a failure management strategy that is typically a subset of RCM; RCM analysis identifies which assets are critical enough to justify the cost of CBM implementation.
Can CBM be performed without real-time sensors?
Yes; CBM can utilize periodic manual inspections (e.g., portable oil analysis, ultrasonic tests) where data is collected near real-time or periodically, rather than continuous embedded monitoring, as long as actions are based on the measured condition.