Predictive Maintenance
Predictive maintenance uses condition data, trends, and analytical methods to estimate when equipment degradation may require maintenance.
What this term means in maintenance
Predictive maintenance uses condition data, trends, and analytical methods to estimate when equipment degradation may require maintenance.
How predictive maintenance works
Predictive maintenance analyzes changes in equipment condition to estimate developing failure and support intervention at the right time.
Common data sources include:
- Vibration
- Temperature
- Lubricant condition
- Electrical current
- Ultrasound
- Pressure and flow
- Process performance
- Sensor and alarm history
Practical example
Vibration trends show increasing bearing-frequency energy over several weeks. The maintenance team reviews the operating load, confirms bearing deterioration, and schedules replacement during an upcoming production stop.
Predictive versus condition-based maintenance
Condition-based maintenance acts when measured condition crosses an agreed threshold. Predictive maintenance attempts to estimate future deterioration or remaining useful life using trends or models. In practice, organizations sometimes use the terms interchangeably.
Requirements
A useful predictive-maintenance program needs:
- Reliable measurements
- Consistent collection methods
- Asset context
- Trained interpretation
- Action rules
- Work-order follow-up
- Confirmation of actual failure condition
Common mistake
Installing sensors does not automatically create predictive maintenance. Data must lead to timely and verified maintenance decisions.
How this term differs
Predictive Maintenance is use of condition trends or analytical models to forecast when intervention will be needed. It is related to Condition-Based Maintenance, Reactive Maintenance, and Corrective Maintenance, but these terms describe different records, measures, roles, strategies, or decisions and should not be used interchangeably.
Related concepts
Related maintenance terms
Keep exploring connected CMMS, reliability, and maintenance planning terms.
Condition-Based Maintenance
Condition-based maintenance is work initiated when inspection, measurement, or monitoring shows that an asset’s condition has reached a defined action threshold.
Failure Rate
Failure rate is the number of failures observed per unit of operating time for an asset or defined equipment population.
Mean Time Between Failures
Mean Time Between Failures, or MTBF, is the average operating time between failures of a repairable asset during a defined period.
Glossary FAQs
- What data is used in predictive maintenance?
Common inputs include vibration, temperature, lubricant analysis, current, ultrasound, pressure, flow, and process-performance trends.
- Does predictive maintenance require artificial intelligence?
No. Trend analysis, thresholds, engineering models, and specialist interpretation can all support predictive maintenance.
- What is the biggest predictive-maintenance mistake?
Collecting sensor data without clear review ownership, action rules, and work-order follow-up.