The research group "Process Control and Data Analysis" at the IOSB develops concepts and software solutions to monitor and optimize production plants and production processes in a holistic way. The aim is to detect or predict errors and anomalies in plants and processes at an early stage (condition monitoring) and to optimize process control. This is intended to increase the availability of the plants, minimize rejects and improve product quality.
All available information sources are used for this purpose: These are firstly measurement data and parameters from the production process and the plants, secondly physically motivated models of the process, and thirdly the expert knowledge of the plant operators. These information sources are linked with methods of machine learning and artificial intelligence.
In our research projects we work out concrete solutions with partners from industry, which are evaluated in practical use. Application domains are for example process engineering processes (e.g. foaming processes, glass drawing processes, bioprocesses) or condition monitoring of wind turbines.