Improved dynamic dependability assessment through integration with prognostics

Jose Ignacio Aizpurua, Victoria M. Catterson, Yiannis Papadopoulos, Ferdinando Chiacchio, Gabriele Manno

Research output: Contribution to journalArticle

9 Citations (Scopus)

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The use of average data for dependability assessments results in a outdated system-level dependability estimation which can lead to incorrect design decisions.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.
LanguageEnglish
Pages1-21
Number of pages21
JournalIEEE Transactions on Reliability
Early online date10 May 2017
DOIs
Publication statusE-pub ahead of print - 10 May 2017

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Power generation
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Keywords

  • prognostics
  • dynamic dependability
  • model to model transformation
  • risk transformation
  • risk monitor
  • remaining useful life
  • condition monitoring

Cite this

Aizpurua, Jose Ignacio ; Catterson, Victoria M. ; Papadopoulos, Yiannis ; Chiacchio, Ferdinando ; Manno, Gabriele. / Improved dynamic dependability assessment through integration with prognostics. In: IEEE Transactions on Reliability. 2017 ; pp. 1-21.
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Improved dynamic dependability assessment through integration with prognostics. / Aizpurua, Jose Ignacio; Catterson, Victoria M.; Papadopoulos, Yiannis; Chiacchio, Ferdinando; Manno, Gabriele.

In: IEEE Transactions on Reliability, 10.05.2017, p. 1-21.

Research output: Contribution to journalArticle

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