Improved dynamic dependability assessment through integration with prognostics

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

doi:10.1109/tr.2017.2693821

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

Professor Yiannis Papadopoulos Y.I.Papadopoulos@hull.ac.uk
Professor

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The use of average data for dependability assessments results in a outdated system-level dependability estimation which can lead to incorrect design decisions.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

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

Journal Article Type	Article
Acceptance Date	Apr 9, 2017
Online Publication Date	May 10, 2017
Publication Date	2017-09
Deposit Date	May 23, 2017
Publicly Available Date	May 23, 2017
Journal	IEEE transactions on reliability
Print ISSN	0018-9529
Publisher	Institute of Electrical and Electronics Engineers
Peer Reviewed	Peer Reviewed
Volume	66
Issue	3
Pages	893-913
DOI	https://doi.org/10.1109/tr.2017.2693821
Keywords	Prognostics; Dynamic dependability; Model to model transformation; Risk monitor; Remaining useful life; Condition monitoring
Public URL	https://hull-repository.worktribe.com/output/451549
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.
Contract Date	May 23, 2017

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