The department Process Optimisation and Digitalisation focuses its research on predictive maintenance strategies. Continuous health monitoring and optimisation of well-established maintenance processes are among the research topics which contribute to the development of innovative MRO methods. The concept of the Digital Twin constitutes the core of the research activities. Thorough analyses of the real product enable the setup of a virtual representation which features all research relevant attributes. The model allows for the recording and processing of collected data, thus providing an efficient and precise interface for further research efforts.
The main research concentrates on the evaluation of heterogeneous data and experiences collected from the analysis of maintenance, repair and operation tasks. Using these data enables the prediction of any maintenance requiring incident including damage and fatigue for every product individually constituting a step forward from current practices drawn on statistic-based forecasts.
Singular maintenance events are adapted and optimised by the means of new technologies to enable their seamless integration into higher-level proves chains. As an example, today’s work-intensive manual documentation and data evaluation methods can be replaced by a fully automized digital workflow, improving the reliability and effectivity of these processes.
The MRO 4.0 research application laboratory provides the means for the hands-on evaluation and demonstration of the investigated research topics.