Machine Health
Condition Monitoring vs Predictive Maintenance: What Is the Difference?
Distinguish current-condition alerts, fault diagnosis and predictions about future maintenance needs.
The terms condition monitoring and predictive maintenance are often used together, but they describe different capabilities. A clear distinction helps set a realistic project scope.
Understand the capability levels
Condition monitoring observes indicators and trends. Diagnosis interprets evidence to identify a possible fault. Prognosis estimates a future outcome, such as deterioration risk within a stated period. These stages need different evidence and validation. An alarm threshold on temperature is condition monitoring even when the data appears in an AI-branded dashboard.
Match the approach to available evidence
Review failure records, maintenance notes, sensor history and operating context. Predictive models may need representative degradation examples or a defensible physical model. Sparse or inconsistent labels limit what can be claimed. A well-maintained rule-based monitoring system can be more useful than an unvalidated remaining-life number.
Define the maintenance decision
Ask what action a warning would change: inspection scheduling, spare procurement or a planned stop. Compare warning time with the lead time for that action. Some failures occur too suddenly for the selected measurement strategy. Keep existing required maintenance and protective measures unless an approved engineering review changes them.
Evaluate outcomes over time
Track confirmed findings, unnecessary inspections, missed issues and useful lead time. For predictions, report uncertainty and performance on data outside development. Record interventions because repair changes the future outcome the model might otherwise have observed. Treat rollout as a measured programme, not a one-time installation guarantee.
FAQ
Do we need AI to start monitoring?
No. Suitable sensors, baselines, reviewed rules and a maintenance response can deliver a useful first stage.
Technical References
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