Improving building performance through the use of a digital twin

The aim of the project is to develop modular and scalable inspection and diagnostic methods for automated operational performance analyses and fault detection and diagnostics (FDD) of technical building installations and systems. A key innovation leap is ensuring a high degree of automation through the targeted use of metadata and model-based analyses. Numerical methods are used in combination with Building Information Modelling (BIM) to independently detect deviations from the ideal operating status at plant and system level and to automatically initiate optimisation and inspection measures. Digitised component and operating data information with defined ontology and semantics serve as the data basis. The resulting universal approach opens up broad access for future cooperation with regional companies. Specifically, the analysis methods can be used by manufacturers for product development, by planners for design reflection and implementation monitoring and by operators for the development of data-driven commissioning, maintenance and servicing strategies. In addition, the project enables the applicant's central building technology expertise to be further expanded in order to focus on digitalisation and to strengthen research-led teaching.