Digitalization of (bio-)processes and plant construction

Our unique selling point

We combine process knowledge with digitalization. We understand your processes and digitize your data for the cost-efficient optimization of your process management. We achieve this with initial data analysis, efficient data communication and simulation-based control using digital twins. 

Data structuring: We create the prerequisites for the application of AI in process technology

In order for analyzed process data to be used for the digital optimization and control of processes, it must first be made accessible to the respective users (process operators, planners, scientists).

To this end, we are creating an organized and process-oriented data structure at Fraunhofer IGB. This is a prerequisite for the use of any AI tools for data evaluation and modelling or simulation. Structuring the available data is therefore a fundamental milestone on the path to the digitalization of processes. 

Data management: We ensure that your data communicate with each other and make it AI-enabled

Our main focus at Fraunhofer IGB is on integrated and process-oriented data management. To this end, we analyze your measurement data and ensure that all data is collected, integrated into the structure and can communicate with each other: The networking of a wide variety of data and protocol formats, automated transfer and backup of plant data (including offline data such as analytics data) create the prerequisites for smart process control and automation as well as efficient data processing (operational analysis, modelling etc.).

Our data management is cost-efficient, as it requires only a small amount of hardware and dispenses with expensive commercial solutions.

We optimize operational management through remote monitoring in real time

Thanks to the efficient data structure, the process data can be used simultaneously for visualization, automation and modelling tasks. We use it to visualize the process, for process optimization through operational analysis and for the development of innovative automation concepts. We use this knowledge to implement system monitoring and system control for your process as remote monitoring in real time.

We select the necessary sensors and actuators in such a way that the right data is collected to control the system. We also develop soft sensors to save costs for complex measurement technology, such as flow sensors. With the right programming, these can calculate the required data from measuring points that have already been collected.

We also develop models, so-called digital twins, which we can use to program a simulation-supported control system in order to optimize your process. This makes it possible to vary process parameters dynamically, for example to minimize energy input or maximize product yield.

Plant planning: design and scenario evaluation through process simulation

We design your system with the required system components. To do this, we balance and model your processes using mass and energy balances. We rely on physical modelling methods, but also use AI tools or hybrid models if required. Using process simulations, we can predict the efficiency of your planned plant and thus increase the profitability of your project. Unpredictable parameters are often also crucial for the optimal operation of plants: different locations, seasons or weather conditions make it necessary to adjust the process control. This dynamic data can be incorporated into our calculations (MatLab/Simulink), enabling us to forecast models for various scenarios with our simulations.