Importances of components and events in non-coherent systems and risk models
Jussi K. Vaurio
Reliability Engineering and System Safety, 2016, vol. 147, issue C, 117-122
Abstract:
Component importance measures have been defined and applied so far mostly for coherent systems. This paper develops and compares possible extensions of the traditional measures to non-coherent systems. The focus is on Birnbaum- and Criticality-type importances, both with respect to system unavailability and system failure intensity. Several versions are suggested for both measure types, each with different interpretation and potential applications. The measures are presented in terms of Boolean system logic functions so that they can be quantified with usual fault tree techniques even for large systems without manually solving and derivation of lengthy analytical functions. Examples demonstrate the method and discover some potential problems in system design if a component can initiate an accident while it is also part of a safety function to prevent an accident. Results are compared to earlier published results obtained with different algorithms.
Keywords: Birnbaum; Criticality; Fault tree; Importance measures; Non-coherent; Risk analysis (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832015003348
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:147:y:2016:i:c:p:117-122
DOI: 10.1016/j.ress.2015.11.007
Access Statistics for this article
Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares
More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().