ENEC is at the forefront of the digital transformation of nuclear operations with the rollout of AI-driven predictive maintenance across its operating fleet. The systems analyze thousands of sensor data points in real time to identify anomalies and predict equipment degradation before failures occur.
Early results show a significant reduction in unplanned downtime and improved capacity factors at pilot plants. The predictive models integrate vibration, temperature, and acoustic data with maintenance histories, enabling engineers to schedule interventions with precision.
"Digital technology is transforming how we operate," said Prof. Raj Krishnamurthy, Chief Technology Officer. "Our AI-driven systems don’t just detect faults — they help us understand the underlying health of our assets so we can act before problems arise."
The program is expected to be deployed across the entire fleet by the end of the year, delivering measurable gains in safety, reliability, and economic performance.
