Extracting Functional Machine Knowledge from STEP Files for Digital Twins.

The current challenges of industrial manufacturing forces producers to optimize and to digitize their facilities. The Digital Twin as a digital representation of both the product and the production is a key enabler to efficiency, flexibility, and sustainability. Unfortunately, the development of Digital Twins is sophisticated and hampered by manual tasks. This paper presents an approach to automatically create digital models of the objects which are to be represented, based on 3D CAD data. Therefore, the CAD data, which is stored as a STEP file, is analysed to extract relevant information for the following graph analysis, which is used to identify components, their dependencies and the resulting functional modules. The graph analysis results will be used in future work to implement a digital twin.