Measures of component importance in repairable multistate systems—a numerical study
Bent Natvig,
Arne B. Huseby and
Mads O. Reistadbakk
Reliability Engineering and System Safety, 2011, vol. 96, issue 12, 1680-1690
Abstract:
Dynamic and stationary measures of importance of a component in a repairable multistate system are an important part of reliability. For multistate systems little has been published until now on such measures even in the nonrepairable case. According to the Barlow–Proschan type measures a component is important if there is a high probability that a change in the component state causes a change in whether or not the system state is above a given state. On the other hand, the Natvig type measures focus on how a change in the component state affects the expected system uptime and downtime relative to the given system state. In the present paper we first review these measures which can be estimated using advanced simulation methods. Extending earlier work from the binary to the multistate case, a numerical study of these measures is then given for two three component systems, a bridge system and also applied to an offshore oil and gas production system. In the multistate case the importance of a component is calculated separately for each component state. Thus it may happen that a component is very important at one state, and less important, or even irrelevant at another. Unified measures combining the importances for all component states can be obtained by adding up the importance measures for each individual state. According to these unified measures a component can be important relative to a given system state but not to another. It can be seen that if the distributions of the total component times spent in the non-complete failure states for the multistate system and the component lifetimes for the binary system are identical, the Barlow–Proschan measure to the lowest system state simply reduces to the binary version of the measure. The extended Natvig measure, however, does not have this property. This indicates that the latter measure captures more information about the system.
Keywords: Importance measures; Repairable systems; Discrete event simulation; Birnbaum measure; Barlow–Proschan measure; Natvig measure (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:96:y:2011:i:12:p:1680-1690
DOI: 10.1016/j.ress.2011.07.006
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