2018/01/12 by Nathalie Cauchi, Cauchi, Nathalie, Khaza Anuarul Hoque +5
Computer Science · Decision Sciences · Engineering · #FOS: Computer and information sciences #FOS: Electrical engineering #Logic in Computer Science (cs.LO) #Risk and Safety Analysis #Safety Systems Engineering in Autonomy #Software Reliability and Analysis Research #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1801.04263
openalex publication_date 2018/01/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Cyber-physical systems, like Smart Buildings and power plants, have to meet\nhigh standards, both in terms of reliability and availability. Such metrics are\ntypically evaluated using Fault trees (FTs) and do not consider maintenance\nstrategies which can significantly improve lifespan and reliability. Fault\nMaintenance trees (FMTs) -- an extension of FTs that also incorporate\nmaintenance and degradation models, are a novel technique that serve as a good\nplanning platform for balancing total costs and dependability of a system. In\nthis work, we apply the FMT formalism to a Smart Building application. We\npropose a framework for modelling FMTs using probabilistic model checking and\npresent an algorithm for performing abstraction of the FMT in order to reduce\nthe size of its equivalent Continuous Time Markov Chain. This allows us to\napply the probabilistic model checking more efficiently. We demonstrate the\napplicability of our proposed approach by evaluating various dependability\nmetrics and maintenance strategies of a Heating, Ventilation and\nAir-Conditioning system's FMT.\n