Reliability Analysis of Cold Standby Compound System

Xu, Jing; Xiao, Zhi Jian

doi:10.4028/www.scientific.net/amr.945-949.1116

Cited by 2 publications

(1 citation statement)

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“…Sensitivity analysis for reliability data uncertainty was also provided. Additionally, in [20][21][22], other authors have respectively focused their work on a "reliability analysis of cold standby compound system", "reliability analysis of a cold standby system attacked by shocks" and a "reliability analysis of a renewable multiple cold standby system".…”

Section: Introductionmentioning

confidence: 99%

Mathematical and Simulation Model for Reliability Analysis of a Heterogeneous Redundant Data Transmission System

Houankpo

Kozyrev

2021

Mathematics

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In the actual study, we carried out a reliability analysis of a repairable redundant data transmission system with the use of the elaborated mathematical and simulation model of a closed heterogeneous cold standby system. The system consists of one repair unit and two different data sources with an exponential cumulative distribution function (CDF) of their uptime and a general independent CDF of their repair time. We consider five special cases of the general independent CDF; including Gamma, Weibull-Gnedenko, Exponential, Lognormal and Pareto. We study the system-level reliability, defined as the steady-state probability (SSP) of failure-free system operation. The proposed analytical methodology made it possible to assess the reliability of the whole system in the event of failure of its components. Specific analytic expressions and asymptotic valuations are obtained for the steady-state probabilities of the system and the SSP of failure-free system operation. A simulation model of the system in cases where it is not workable to obtain expressions for the steady-state probabilities of the system in an explicit analytical form was considered, in particular for constructing the empirical system reliability function. The issue of sensitivity analysis of reliability characteristics of the considered system to the types of repair time distributions was also studied. The simulation modeling was done with the R statistics package.

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Section: Introductionmentioning

confidence: 99%