Asset Health Monitoring for Predictive Maintenance
Predictive maintenance is the process of monitoring in-service asset health and using the data to determine when preventive maintenance should be performed. This approach promotes cost savings over routine or time-based scheduling; maintenance tasks can be performed on an as-needed basis while still minimizing the risk of unplanned outages.
Curtiss-Wright has more than 35 years of experience providing innovative products and technologies for the global power industry. Our FAMOS suite of integrated solutions analyze and optimize plant performance to improve equipment reliability and reduce downtime. Using condition monitoring technology, plants can leverage vasts amount of data for early detection of issues or anomalies and optimal maintenance scheduling.
Case Study
Discover how the WA Parish Generating Station improved plant performance by integrating Curtiss-Wright's Fleet Asset Management and Optimization Solutions (FAMOS) suite with other applications, revealing subtle anomalies and power losses.
Case Study
Learn how Exelon used the FAMOS thermal performance and condition monitoring suite to consolidate their resources while also increasing their performance visibility - allowing them to improve their capabilities while lowering costs.
Case Study
Find out how SaskPower used Curtiss-Wright's Fleet Asset Management and Optimization Solutions (FAMOS) thermal performance and monitoring suite to optimize man-hours and reduce unexpected outages.