End User
CPO
Description
This AI-driven service continuously analyses the frequency and patterns in incoming observations from offshore renewable energy systems. It predicts the likelihood of component failure by correlating real-time and historical data, enabling predictive maintenance strategies. This reduces unexpected downtimes and extends the operational life of offshore assets. The system can also prioritize assets based on risk levels and maintenance urgency.
Core Capabilities
Monitoring & Anomaly Detection
Predictive & Prescriptive Analytics
Automation & Control Systems
Business Need
Offshore energy systems are subject to harsh conditions and hard-to-access infrastructure. This service addresses the need for early malfunctioning identification and dispatch efficiency by allowing remote detection, prioritization of maintenance tasks, and improved operational safety.
Key Performance Indicators
Anomaly prediction accuracy (confusion matrix)
Mean time between failures (MTBF) improvement
Maintenance cost reduction estimate
Data Provided
Real-time sensor data from wave plant turbines (power generation, weather conditions, wave size, etc.)
Historical power generation and weather/wave data
Open-source weather forecasts
AI-based weather forecasts (Optional)
Proprietary datasets from plant operations (Optional)
Maintenance records (Optional)
Anomaly detection logs (Optional)
TEF
TEF RES