Student
Application of Reduced-Order Modeling in Context of Plastics Profile Extrusion
Please login to view abstract download link
In scope of this conference presentation, we will present our latest findings on the implementation of a physics-informed neural network (PINN) as a reduced-order model in context of the plastic profile extrusion (PPE) process. In context of the PPE process, the PINN can provide additional process information at process time that cannot be accessed by conventional measurements. In scope of this talk, we discuss the PINN model, the industrial context, and how the PINN can be embedded in the concept of digital shadows/digital twins.
