Reliable anomaly detection with low false alarm & troubleshooting for a critical air-blower that feeds combustion air to major parts in the refinery.
A semi-supervised anomaly detection solution based on expert-annotations provides alerts in real-time for deviations from normal behavior. A cause for the deviation is also indicated.
Automatically optimize & control the energy consumed by electrolyzers at a chlorine plant based on their predicted health, the energy price variations in the R2 imbalance market & the production targets.
A predictive model for the health of the electrolyzers was developed & the energy consumption was optimized based on mathematical & data driven models. Further a mathematical optimization was performed in order to account for fluctuations in energy prices, customer orders & storage.