Maintenance of Smart Buildings using Fault Trees

Nathalie Cauchi, Khaza Anuarul Hoque, Mariëlle Stoelinga, Alessandro Abate

    Research output: Contribution to conferencePaper

    1 Citation (Scopus)
    24 Downloads (Pure)

    Abstract

    Timely maintenance is an important means of increasing system dependability and life span. Fault Maintenance trees (FMTs) are an innovative framework incorporating both maintenance strategies and degradation models and serve as a good planning platform for balancing total costs (operational and maintenance) with dependability of a system. In this work, we apply the FMT formalism to a Smart Building application and propose a framework that efficiently encodes the FMT into Continuous Time Markov Chains. This allows us to obtain system dependability metrics such as system reliability and mean time to failure, as well as costs of maintenance and failures over time, for different maintenance policies. We illustrate the pertinence of our approach by evaluating various dependability metrics and maintenance strategies of a Heating, Ventilation, and Air-Conditioning system.1
    Original languageEnglish
    Pages28:1-28:25
    DOIs
    Publication statusPublished - 2018
    Event4th ACM International Conference on Systems for Energy-Efficient Built Environments 2017 - TU Delft Aula Congrescentrum, Delft, Netherlands
    Duration: 8 Nov 20179 Nov 2017
    Conference number: 4
    http://buildsys.acm.org/2017/

    Conference

    Conference4th ACM International Conference on Systems for Energy-Efficient Built Environments 2017
    Abbreviated titleBuildSys 2017
    CountryNetherlands
    CityDelft
    Period8/11/179/11/17
    Internet address

    Keywords

    • Maintenance
    • Fault Tree Analysis
    • Stochastic model checking

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  • Cite this

    Cauchi, N., Hoque, K. A., Stoelinga, M., & Abate, A. (2018). Maintenance of Smart Buildings using Fault Trees. 28:1-28:25. Paper presented at 4th ACM International Conference on Systems for Energy-Efficient Built Environments 2017, Delft, Netherlands. https://doi.org/10.1145/3232616