  Digital Twins are increasingly being introduced for smart manufacturing
systems to improve the efficiency of the main disciplines of such systems.
Formal techniques, such as graphs, are a common way of describing Digital Twin
models, allowing broad types of tools to provide Digital Twin based services
such as fault detection in production lines. Obtaining correct and complete
formal Digital Twins of physical systems can be a complicated and time
consuming process, particularly for manufacturing systems with plenty of
physical objects and the associated manufacturing processes. Automatic
generation of Digital Twins is an emerging research field and can reduce time
and costs. In this paper, we focus on the generation of Digital Twins for
flexible manufacturing systems with Automated Guided Vehicles (AGVs) on the
factory floor. In particular, we propose an architectural framework and the
associated design choices and software development tools that facilitate
automatic generation of Digital Twins for AGVs. Specifically, the scope of the
generated digital twins is controlling AGVs in the factory floor. To this end,
we focus on different control levels of AGVs and utilize graph theory to
generate the graph-based Digital Twin of the factory floor.
