The project aimed to create an advanced model by utilizing data in combination with physical and chemical principles, to be capable of estimating the purity of the bottom product in a distillation column. This model offered valuable insights into the column’s operations, revealing a deeper understanding of the underlying process. Scientia Industrial Technologies demonstrated extensive expertise in process technology throughout the project. They showcased their ability to gain a thorough understanding of the complexities within the distillation process and effectively integrate this knowledge into the model, allowing it to uncover relevant aspects.
We improve chemical process operation by filling in missing information using next-generation, tailor-made AI models that combine data with process knowledge for enhanced accuracy and efficiency.