SPP 2364:  Autonomous processes in particle technology - Research and testing of concepts for model-based control of particulate processes

• Subject Area: Thermal Engineering/Process Engineering ; Computer Science, Systems and Electrical Engineering
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 460890345

The aim of Priority Program is the research and testing of methods for autonomous process control in particle technology. The distributed properties of particles often prevent extensive automation and autonomous process control during their processing, which appears necessary for independent adjustment of product properties without external intervention. In the first period, the SPP was divided into three subject areas: the development of controllable models (modeling), measurement systems for the in-situ recording of product properties (measurement technology) and the development of concepts for the model-based control of particle technology processes (process control). The aim was to close the control loop by linking the three topics as a fundamental structural element. In the first phase it was the intention to provide the proposed processes and equip them with appropriate actuators and sensors so that the control technology could intervene directly. In the second phase of the SPP, the focus is on process chains consisting of two or more basic operations. The integration of equipment and information technology into a process chain enables the interactions between the basic operations and their mutual influence to be investigated. An optimum operating point for an individual process step does not guarantee an optimal operation of the entire chain. At this point, extensive research work is conceivable, such as the investigation of the non-linear behavior of a process step in interaction with the other basic operations or with the material return, the behavior of disturbances within a basic operation and their effect on the entire chain or the investigation of the interactions between the digital representation and the real process within a given operating window. After completion of the program, a new type of "scientific toolbox" (methods, algorithms, models, data structures and information architectures) should be available that enables reliable process control, whereby the tool should also be transferable to new particle processes. The SPP brings together the necessary expertise from various research fields in particle technology, control engineering and computer science.

• DFG Programme: Priority Programmes

Projects

• Adaptive data-driven predictive control using behavioral approach for autonomous powder compaction (Applicants Bajcinca, Naim ;  Thommes, Markus )
• Adaptive Optimal Control of Continuous Aqueous Two-Phase Flotation (ATPF) (Applicants Diehl, Moritz ;  Nirschl, Hermann )
• ARCO-CHAIN: Autonomous robust predictive control of a continuous crystal process chain (Applicants Lucia Gil, Sergio ;  Wohlgemuth, Kerstin )
• Autonomous and self-adapting, high-resolution 3D additive manufacturing by high energy impacts of fine particles (Applicants Antonyuk, Sergiy ;  Palis, Stefan )
• Autonomous control of a process chain for CO2 mineralization by use of alkaline waste materials (Applicants Bajcinca, Naim ;  Gleiß, Marco ;  Sundmacher, Kai )
• Autonomous structure formation processes in spray fluidized bed agglomeration (Applicants Bück, Andreas ;  Kienle, Achim ;  Tsotsas, Evangelos )
• Coordination Funds (Applicant Nirschl, Hermann )
• Formulation of dispersed systems via (melt) emulsification: Process design, in situ diagnostics and regulation (Applicants Graichen, Knut ;  Huber, Franz ;  Schmidt, Jochen )
• Model-based control of spray synthesis of structured granules with specified properties, using transfer functions derived by multivariate stochastic models and machine learning (Applicants Peuker, Urs ;  Schmidt, Volker )
• Model-based control of the dynamics during fine grinding in wet-operated stirred media mills (Applicants Kirches, Christian ;  Schilde, Carsten )
• Model-based process control for dynamic and efficient operation of liquid/liquid mixer-settler systems (Applicants Knorn, Steffi ;  Kraume, Matthias )
• Model-based Process Control for Transferred Arc Synthesis of Nanoparticles (Applicants Ding, Steven Xianchun ;  Kruis, Frank Einar )
• Model-based quality control in continuous manufacturing of pharmaceutical granules and tablets (QC4CM) (Applicants Klinken-Uth, Stefan ;  Stemmler, Sebastian )
• Optimization of Gas-Solid Fluidized Beds Operation using Machine Learning (Applicants Mostaghim, Sanaz ;  van Wachem, Berend )
• Synthesis and purification of highly functional nanoparticles: a controlled process chain from sol-gel synthesis to dead-end ultrafiltration (Applicants Meurer, Thomas ;  Nirschl, Hermann )

• Spokesperson: Professor Dr.-Ing. Hermann Nirschl