ANNEA - Predictive maintenance and underperformance detection
The next-generation predictive maintenance platform
ANNEA helps renewable energy companies to reduce operation & maintenance costs, optimize operations, and, therefore, make green energy more affordable. Connecting to the existing sensors, we create a digital twin of each machine to perform real-time failure prediction, underperformance detection, and its root causes.
Our solution is based on a combination of physical models, normal behavior models, and data-driven self-learning AI models. This combination enables more reliable and precise forecasts comparing to other solutions in the market.
Specification Title | Specification Description |
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Areas of Application
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Wind energy sector (onshore & offshore); Solar energy, Green hydrogen co-production.
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Prediction
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On average 120 days before the failure. | Close to 0% false-positives.
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Flexibility
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Adaptable across the renewable energy sectors. | The dashboard is fully customizable: the variables are shown according to the clients' needs and in the required language.
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Software
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SaaS model.
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Asset Life Extension
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Increased due to the failures predictions and preventions.
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Condition Based Maintenance
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A health index is calculated and shown for each asset together with the maintenance/repair recommendations.
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Modelling
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Cross-modelling approach: a mix of normal behavior models with AI and physical models.
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Accessibility
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Adaptable solution deployment, depending on the client's IT architecture.
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Acquisition System
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Connecting to the sensors that are already installed in the renewable assets.
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Deployment
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Can be done on-premise or client's cloud or ANNEA cloud.
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Reviews
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The Technology Readiness Level (TRL) indicates the maturity level of novel technologies. Learn more about the TRL scale used by us.
[8/9]
Relative Business Impact
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