By training AI models on the real-world historical data from a plant, we add an additional intelligent layer to your operations improving and automating decision-making in real time. Our solution optimize the processes, such as throughput, energy or raw material use and also combine it with external factors where relevant.
We connect to control system data, subsystems and also to external data sources where relevant.
Many process models have been created when there was less data available, These models are also often hand crafted by experts. With more data and machine learning it is often possible to improve the models e.g. improve energy distribution in district heating networks through improved distribution models. Recipes can also be more efficiently controlled compared to e.g. step models.