Completed funded project

The European process industry faces the challenge of continuously improving its resource and energy efficiency in order to remain economically successful and help achieve the EU's climate and environmental objectives. A promising approach to this is the automated, plant-wide control of resource-intensive processes with algorithms that use machine learning. Key to the success of this concept are, on the one hand, the measuring methods and sensors for recording the required information and, on the other hand, physical models that enable process control during regular plant operation.

• Overall objectives of the project consortium:
  
  • Development of a software toolbox for monitoring and optimised process control in different industrial plants
    
  • Further development and testing of sensor systems (TOM, FOM, RF, NIR)
    
  • Tests in industrial plants of the project partners / Demonstration of the potential for other sectors, e.g. for the ceramics industry
    
• Subgoals of the Fraunhofer-Centre HTL
  
  • Development of methods for detection and modelling of hot gas corrosion processes
    
  • Development of in-situ control methods for ceramic production
    
  • Integration of the sensor systems in FuDiPO-Toolbox