Simulation-based Digital Twin for Production and Logistics Material Flows
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Updated
Apr 27, 2026 - Python
Simulation-based Digital Twin for Production and Logistics Material Flows
Facsimile Simulation Library
Simulation framework for evaluating pool sequencing and shop floor dispatching rules in disassembly
In this project a Machine Learning model is trained for learning a simulator for Material-Flow systems, where the Machine Learning model is based on Graph Neural Networks. The data for training the model is generated using an accurate physicbased simulator.
Public-safe civic infrastructure production studies covering recycling automation, 3D-print workflows, material flow, QA boundaries, and Foundation-adjacent engineering separation.
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