Aveva Predictive Analytics (APA)
Description
A means to predict and prevent failure is at the forefront of operations and maintenance. One of the best economical means to accomplish this is through data anomaly detection and predictive maintenance for power generation applications.
Detailed example
Anomaly detection, fault diagnostics, analysis of startup/shutdown conditions, configurable model frequencies, alerts, case management, etc.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The maintenance savings to Reclamation for the successful implementation of predictive maintenance is estimated to exceed $60 million dollars per year when implemented across Reclamation’s hydropower fleet.
Controls / human review
ATO: No; PIA: Not published