The System Reliability Department develops system reliability analytics and reliability engineering for mechanical engineering systems, with a focus on sustainability and circularity. Proven methods such as probabilistic FMEA are supplemented by approaches that take uncertainties into account and combine load and stress analyses with experimental system analyses under complex conditions. A key goal is the digitalization of testing and validation procedures and the use of AI and machine learning (ML) for virtualized system reliability analysis. This allows reliability engineering to be anchored early and centrally in the development process and supports the development of complex, safety-critical systems more efficiently and quickly.