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Improved dynamic dependability assessment through integration with prognostics

Aizpurua, J. I.; Catterson, V. M.; Papadopoulos, Y.; Chiacchio, F.; Manno, G.

Authors

J. I. Aizpurua

V. M. Catterson

F. Chiacchio

G. Manno

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The use of average data for dependability assessments results in a outdated system-level dependability estimation which can lead to incorrect design decisions.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 interdependencies, 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.

Journal Article Type Article
Publication Date 2017-09
Journal IEEE transactions on reliability
Print ISSN 0018-9529
Electronic ISSN 1558-1721
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 66
Issue 3
Pages 893-913
Institution Citation Aizpurua, J. I., Catterson, V. M., Papadopoulos, Y., Chiacchio, F., & Manno, G. (2017). Improved dynamic dependability assessment through integration with prognostics. IEEE Transactions on Reliability, 66(3), 893-913. https://doi.org/10.1109/tr.2017.2693821
DOI https://doi.org/10.1109/tr.2017.2693821
Keywords Prognostics; Dynamic dependability; Model to model transformation; Risk monitor; Remaining useful life; Condition monitoring
Publisher URL http://ieeexplore.ieee.org/document/7924411/
Additional Information This is the accepted manuscript of an article published in: IEEE transactions on reliability, 2017, v.66, issue 3.

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