Definition
Predictive maintenance uses condition data, historical events, and analytical models to estimate future maintenance needs. Work is planned as close as practical to the actual need without waiting for failure.
Key facts
- It depends on reliable sensor, process, and maintenance data.
- It forecasts a development rather than only reacting to a threshold.
- Maintenance windows and spare parts can be prepared earlier.
- Data quality and a clear operational use case matter more than model complexity.
Why does Predictive maintenance matter in maintenance?
Measurements such as vibration, temperature, or current draw are connected with operating states and past failures. Models detect changes and estimate risk or remaining useful life.
How do maintenance teams apply Predictive maintenance?
The method is most valuable for critical assets with measurable deterioration signals, sufficient history, and high downtime costs. Not every component needs a prediction model.
What is good practice for Predictive maintenance?
A clearly scoped failure mode is a better starting point than a plant-wide sensor initiative. Predictions must translate into work orders, planning decisions, and ownership to create operational value.