Predictive maintenance solution for dynamic equipment, developing fault prediction models from the data from the monitoring systems deployed at the plant.
It enables:
- Maintenance costs and unexpected faults to be reduced by 50%.
- Repair and reconditioning time to be reduced by 60%.
- Spare part inventory to be reduced by 30%.
- Activity time to be increased by 30%.
This project, developed in conjunction with PETRONOR, has the following objectives:
- Develop an automatic fault diagnosis system in dynamic equipment based on Condition Monitoring (CM) data, which also enables the asset’s health footprint to be generated.
- Develop an automatic fault prognosis system, based on the information obtained through physical models, including the severity of the faults identified and their estimated evolution in accordance with the operation conditions.
The dynamic equipment on which the monitoring system is deployed include:
- Centrifugal pump: generating scalable diagnosis solutions.
- Blowers or extractors: critical equipment; a fault in them is high impact.
- Electric motors associated with pumps, blowers and extractors.
