Dependability estimation for non-Markov consecutive-k-out-of-n: F repairable systems by fast simulation

Gang Xiao, Zhizhong Li and Ting Li

Reliability Engineering and System Safety, 2007, vol. 92, issue 3, 293-299

Abstract: A model of consecutive-k-out-of-n: F repairable system with non-exponential repair time distribution and (k-1)-step Markov dependence is introduced in this paper along with algorithms of three Monte Carlo methods, i.e. importance sampling, conditional expectation estimation and combination of the two methods, to estimate dependability of the non-Markov model including reliability, transient unavailability, MTTF, and MTBF. A numerical example is presented to demonstrate the efficiencies of above methods. The results show that combinational method has the highest efficiency for estimation of unreliability and unavailability, while conditional expectation estimation is the most efficient method for estimation of MTTF and MTBF. Conditional expectation estimation seems to have overall higher speedups in estimating dependability of such systems.

Keywords: Dependability; Consecutive-k-out-of-n: F repairable system; Non-Markov system; Importance sampling; Conditional expectation estimation (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:92:y:2007:i:3:p:293-299

DOI: 10.1016/j.ress.2006.04.004

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