Abstract
Machine Learning ML algorithms can be combined with the modular automation protocol MTP and recognize the flooding behavior of laboratory fluids separation columns. Hence, artificial intelligence AI tools with deep learning DL offer a high potential for the process industry and allow to capture operating states that are otherwise difficult to detect or model. However, the advanced methods are only hesitantly applied in practice. This article provides an overview on how artificial intelligence-based algorithms can be implemented in existing laboratory plants. Process sensor data as well as image data are used to model the flooding behavior of distillation and extraction columns and the system is adapted to the existing modular automation standard of the Module Type Package MTP.
Topical Heading
Separations: Materials, Devices and Processes
Keywords Clustering, Convolutional neural networks, Flooding, Process monitoring, Time series forecasting
1Department of Biochemical and Chemical Engineering, Laboratory of Equipment Design, TU Dortmund University, Emil-Figge-Strasse 68, Dortmund, 44227, Germany
All authors contributed equally