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We developed a unique combination of deep learning, survival modelling, sequence analysis, risk prediction and visualisation to predict part failures and take action
About
We developed a cutting edge approach to predict when power production equipment will fail, which allows maintenance crews to take corrective action. This allows the maintenance team to prioritise activities rather than follow a routine maintenance schedule. As a result, low-risk equipment can increase uptime and power generation, while high-risk equipment receives targeted interventions to avoid costly unexpected outages. Our expert system contains huge operational and maintenance datasets from generators, turbines, and transformers across many manufacturers, giving us a vendor-agnostic approach to fault prediction which moves well beyond standard condition-based monitoring.
Key Benefits
Predict fault and failures of power production equipment, reduce downtime for scheduled maintenance, discover causes of unexplained damage, prioritise targeted maintenance activities.
Applications
Predictive maintenance in hydropower production