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Advanced Pattern Recognition for Predictive Maintenance
Risk prevention is one of the most efficient strategies to reduce costs and maintain plant safety. FAMOS’s PdP software uses advanced real-time pattern recognition based on existing data and history to provide an updated, real-time analysis of both current and potential future states of system operation. Using this advanced pattern recognition technology, PdP can predict system failures to help schedule maintenance and outages, and decrease the amount of corrective, unscheduled maintenance forced on a user’s sites, reducing cost and lost time, as well as improving safety.
Benefits
Using PdP technology, power plants can reduce control room alarms, increase plant productivity, and lower the likelihood of property loss and serious injury caused by catastrophic failure.
PdP’s early identification of anomalies means potential catastrophic failures can be avoided by scheduling repairs and averting costly unplanned shutdowns.
The PdP software's advanced notification system for potential failures allows plant operators to schedule maintenance effectively and efficiently, while avoiding costs associated with unplanned outages and catastrophic failures.
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.
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.
