  Cyber-physical systems, like Smart Buildings and power plants, have to meet
high standards, both in terms of reliability and availability. Such metrics are
typically evaluated using Fault trees (FTs) and do not consider maintenance
strategies which can significantly improve lifespan and reliability. Fault
Maintenance trees (FMTs) -- an extension of FTs that also incorporate
maintenance and degradation models, are a novel technique that serve as a good
planning platform for balancing total costs and dependability of a system. In
this work, we apply the FMT formalism to a Smart Building application. We
propose a framework for modelling FMTs using probabilistic model checking and
present an algorithm for performing abstraction of the FMT in order to reduce
the size of its equivalent Continuous Time Markov Chain. This allows us to
apply the probabilistic model checking more efficiently. We demonstrate the
applicability of our proposed approach by evaluating various dependability
metrics and maintenance strategies of a Heating, Ventilation and
Air-Conditioning system's FMT.
