Improved dynamic dependability assessment through integration with prognostics

Aizpurua, Jose Ignacio and Catterson, Victoria M. and Papadopoulos, Yiannis and Chiacchio, Ferdinando and Manno, Gabriele (2017) Improved dynamic dependability assessment through integration with prognostics. IEEE Transactions on Reliability. pp. 1-21. ISSN 0018-9529 (https://doi.org/10.1109/TR.2017.2693821)

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Abstract

The use of average data for dependability assessments results in a outdated system-level dependability estimation which can lead to incorrect design decisions. With increasing availability of online data, there is room to improve traditional dependability assessment techniques. Namely, prognostics is an emerging field which provides asset-specific failure information which can be reused to improve the system level failure estimation. This paper presents a framework for prognostics-updated dynamic dependability assessment. The dynamic behaviour comes from runtime updated information, asset inter-dependencies, and time-dependent system behaviour. A case study from the power generation industry is analysed and results confirm the validity of the approach for improved near real-time unavailability estimations.

ORCID iDs

Aizpurua, Jose Ignacio ORCID logoORCID: https://orcid.org/0000-0002-8653-6011, Catterson, Victoria M. ORCID logoORCID: https://orcid.org/0000-0003-3455-803X, Papadopoulos, Yiannis, Chiacchio, Ferdinando and Manno, Gabriele;
  • Item type:Article
    ID code:60422
    Dates:
    Date
    Event
    10 May 2017
    Published
    10 May 2017
    Published Online
    9 April 2017
    Accepted
    Notes:© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:11 Apr 2017 09:35
    Last modified:11 Nov 2024 11:40
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/60422
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