Combining automatic model generation and model adaption for simulation-based digital twins of machine tools

In the manufacturing industry, virtual commissioning has become an established method for the efficient qualification of control software. Usually, a Software-in-the-loop simulation is used that combines kinematics and behavior models with a virtual control. This simulation virtually represents the structure, properties and behavior of a specific machine tool variant and has the potential to be reused during the operation as a simulation-based Digital Twin. However, the Digital Twin requires that the simulation models are frequently updated during operation whenever changes at the real machine tool occur. To address this challenge, this paper presents an approach that combines automatic model generation and model adaption. Model generation is needed to reconfgure the simulation model whenever physical components are changed during maintenance. Model adaption is used to optimize simulation model parameters by gathering and comparing real and virtual sensor data. With the combination of both methods, the simulation-based Digital Twin is kept up-to-date without the effort to manually change parts of the simulation model or adjust model parameters.