TY - JOUR
T1 - Barlow and Proschan principle for coherent systems with statistically dependent component and redundancy lifetimes
AU - You, Yinping
AU - Li, Xiaohu
N1 - Publisher Copyright:
© The Author(s), 2024. Published by Cambridge University Press.
PY - 2024
Y1 - 2024
N2 - For coherent systems with components and active redundancies having heterogeneous and dependent lifetimes, we prove that the lifetime of system with redundancy at component level is stochastically larger than that with redundancy at system level. In particular, in the setting of homogeneous components and redundancy lifetimes linked by an Archimedean survival copula, we develop sufficient conditions for the reversed hazard rate order, the hazard rate order and the likelihood ratio order between two system lifetimes, respectively. The present results substantially generalize some related results in the literature. Several numerical examples are presented to illustrate the findings as well.
AB - For coherent systems with components and active redundancies having heterogeneous and dependent lifetimes, we prove that the lifetime of system with redundancy at component level is stochastically larger than that with redundancy at system level. In particular, in the setting of homogeneous components and redundancy lifetimes linked by an Archimedean survival copula, we develop sufficient conditions for the reversed hazard rate order, the hazard rate order and the likelihood ratio order between two system lifetimes, respectively. The present results substantially generalize some related results in the literature. Several numerical examples are presented to illustrate the findings as well.
KW - Active redundancy
KW - archimedean copula
KW - coherent system
KW - minimal cut decomposition
KW - reversed hazard rate order
KW - usual stochastic order
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U2 - 10.1017/S0269964824000159
DO - 10.1017/S0269964824000159
M3 - Article
AN - SCOPUS:85212114905
SN - 0269-9648
JO - Probability in the Engineering and Informational Sciences
JF - Probability in the Engineering and Informational Sciences
ER -