Ecological Interface Design für Konditionierungsparameter von Fregatten

Hybrid learning-based digital twin for manufacturing process: Modeling framework and implementation

“…The machining process with geometrically defined cutting edges is described via the cutter-workpiece engagement along the trajectory in the interaction of machine and process. Conventionally, the coupled simulation of drive control and process model with the machine model uses time-consuming machine structure dynamics and process model, normally in the form of FEM (finite element method) and MBS (multibody simulation), as well as the measured characteristics results for calibrating the numerical models regarding machine, tool, and workpiece [24,49]. Therefore, the corresponding DT modeling requires certain simplifications to meet domain-specific real-time requirements while retaining task-specific model granularities.…”

“…The treatment of these process-specific terms depends on manufacturing requirements and available production resources. Via certain simplifying and reconstructing cosimulations of virtual machine tools and machining process [24,49], we define the general modeling strategy for hybrid learning-based DT modeling for machining process that flexibly adapts to dissimilar production scenarios as well as the production data landscape. In the next section, we present our proposed framework to handle these modeling pipelines and heterogeneous data sources involved.…”