Controller integrated digital twin for online optimization of forming processes

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The current individualization of products causes smaller batch sizes and leads to larger numbers of variants and demands further improvement of productivity in the sheet metal forming business. Dynamic effects, fluctuations in material properties, control deviations and wear-related changes in the properties of the machine and tool, that influence accuracy, make experience-based prediction of production parameters virtually impossible. Simulation models are widely used for today’s analysis of machines, processes, and their interactions as well as for the virtual commissioning of machine controls. These models can predict machine states and the forming result with high accuracy. However, there is a lack of manageable methods for the creation and calculation of holistic system simulation models that make the process and all the production equipment involved analyzable. If the virtual images of machines, processes and their interactions can be computed with a holistic real-time system-simulation model and can the model be implemented on the machine control as a synchronous running digital twin, then predictions of the process parameters can be made within a few strokes and a process control can be implemented. This will help to shorten tool ramp-up times, to reduce scrap and to increase the efficiency of sheet metal forming processes significantly. The objective of the project is to create a real-time control-integrated system simulation environment for forming technologies that enables online process control based on the predictions of the production line’s digital twin. A model library will be developed and implemented in the control system of a demonstrator machine. The library will provide real-time simulations of two exemplary processes for sheet metal part production - deep drawing and shear cutting - coupled with a machine simulation in a system simulation. The simulation environment for control-integrated numerical calculations will provide the technical basis for stroke-to-stroke process control.The success of the project is linked to significantly shortening the production start-up time after tool change. The real-time reaction of the system to fluctuations in material and environmental conditions leads to the avoidance of production errors with the aim of zero error production.