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Equipment Anomaly Detection

Created by Arizona Public Service (APS) employees at Palo Verde Nuclear Power Plant, Equipment Anomaly Detection (EAD) technology uses machine learning to detect anomalies in plant equipment and systems, allowing operators to improve performance and prevent failures. Through an exclusive agreement with APS, Curtiss-Wright has added this EAD technology to the FAMOS suite of thermal plant performance and condition monitoring solutions. The EAD platform is currently in production with a new release scheduled for Fall 2020.


Using advanced artificial intelligence (AI) technology, the EAD platform uses machine learning to monitor plant equipment and systems and automatically identify abnormal conditions or activity.

The Equipment Anomaly Detection technology offers rapid detection of potential issues - before they cause problems to plant equipment or systems. By enabling preventative maintenance practices, the EAD platform allows plants to increase efficiency and reliability while improving performance and reducing costs.

EAD technology supports equipment condition monitoring applications as well as plant-wide modernization and digitalization strategies.

News Announcement

BREA, CA ­­– January 31, 2020 – Curtiss-Wright Corporation announced it has signed an exclusive agreement with Arizona Public Service Company (APS) to commercialize APS’s equipment anomaly detection (EAD) technology... Read more