Implementation of residual stress models in a technological material removal simulation

Digital twins of machined workpieces are increasingly used due to their potential for sustainable optimization of manufacturing processes. They empower to store process knowledge and enable the prediction of properties of the real counterpart by using derived process models. Quality influencing factors such as process induced residual stresses and deformation can be detected and even counteracted by digitally mirroring the manufacturing process. The results and methods presented in this publication are based on a complex process chain for the milling of thin-walled structural aerospace components. Residual stress measurement data are recorded along the real process chain and stored in a digital twin in order to be utilized in accompanying simulations. In this paper, a simulation-based digital workpiece twin is presented, which is empowered by process-relative and location-continuous residual stress models. The focus is on the realization of data interfaces along the digital process chain. Thus, an architecture scheme is being introduced, which maps the data transfer of residual stress measurement data, from a dexel-based machining simulation to a FE-based deformation simulation. The digital workpiece twin serves as an enabler of the process chain. Residual stress predictions can be mapped with a determination accuracy of 80% in the digital twin. Additionally it is used as a tool for the flexible adaptation of acquired process knowledge to varying thin-walled aerospace components.