2016
DOI: 10.1109/tr.2016.2570545
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Reliability Modeling on Consecutive-<inline-formula> <tex-math notation="LaTeX">$k_r $</tex-math> </inline-formula>-out-of-<inline-formula> <tex-math notation="LaTeX">$n_r $</tex-math> </inline-formula>:F Linear Zigzag Structure and Circular Polygon Structure

Abstract: We propose the consecutive-k r -out-of-n r :F linear zigzag structure and circular polygon structure, which extend the consecutive-k-out-of-n:F system model. By employing the finite Markov chain imbedding approach, we have proven the equations for calculating the reliability of consecutive-k-out-of-n:F system with different patterns given the state of the first and(or) the last component(s). Based on those reliability equations, we provide the rules for obtaining the reliability of the linear zigzag structure … Show more

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Cited by 39 publications
(19 citation statements)
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“…The reliabilities of SC=lin=con=k=n : F and SC=cir=con=k=n : F systems, are derived by employing the finite Markov chain imbedding approach for statistically independent and Markovdependent cases. These provide extensions of known results for the independent case given by Lin et al 16 and Yin and Cui 6 ; Unified and explicit reliability formulas are derived for the considered linear and circular systems by redefining the state space of the Markov chain, instead of listing all disjoint cases, which makes it to be computationally superior to exhaustive and sum of disjoint products methods; Table 1. Differences between the method developed here and those of Lin et al 16 and Yin and Cui.…”
Section: Introductionmentioning
confidence: 74%
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“…The reliabilities of SC=lin=con=k=n : F and SC=cir=con=k=n : F systems, are derived by employing the finite Markov chain imbedding approach for statistically independent and Markovdependent cases. These provide extensions of known results for the independent case given by Lin et al 16 and Yin and Cui 6 ; Unified and explicit reliability formulas are derived for the considered linear and circular systems by redefining the state space of the Markov chain, instead of listing all disjoint cases, which makes it to be computationally superior to exhaustive and sum of disjoint products methods; Table 1. Differences between the method developed here and those of Lin et al 16 and Yin and Cui.…”
Section: Introductionmentioning
confidence: 74%
“…Lin et al 16 Yin and Cui The method developed here is simpler and more efficient than those of Lin et al 16 and Yin and Cui, 6 which involve too many cases and the corresponding reliability formulas are far too complex;…”
Section: Itemmentioning
confidence: 98%
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