Motivation – Additive manufacturing processes such as FFF are among the modern production processes. Their integration into cyber-physical production systems requires transparency and standardization. Digital twins offer great potential here for consistently mapping control, monitoring, simulation, and analysis in digital form. The work builds on existing research at the institute and aims to develop a transferable, standards-based approach to modeling additive manufacturing machines.

Tasks and objectives – The goal is to develop a generic, standards-based digital twin for additive manufacturing machines based on OPC UA and AAS. The digital twin should enable simulation, control, monitoring, and analysis and will be implemented using two FFF printers as examples. You will analyze relevant standards and tools, derive requirements, and develop a modular framework for reusability across machine types. The prototype implementation will be validated in practice at the institute and critically evaluated with regard to interoperability and expandability.

Requirements:

• Programming skills, e.g., in Python, C++, or JavaScript

• Interest in additive manufacturing (e.g., FFF) and digital twins

• Independent, structured way of working and willingness to learn new technologies