Predictive maintenance is usually associated with sensor investment first. Yet in most plants, maintenance records, production stoppages and quality data are already recorded. The first model can often be built with that existing data.
Practical steps to start
- Consolidate historical failure and maintenance records into one structure
- Start with the equipment carrying the highest downtime cost
- Define the pre-failure symptom window together with the maintenance team
- Use the first model for pattern discovery, not alerting
- Weigh false alarm cost alongside missed failure cost
Sensor investment becomes far more accurate once you have learned which data is genuinely missing.