TY - GEN
T1 - Reliability analysis for dependent competing failure processes with two-stage degradation and external shocks
AU - Wang, Yukun
AU - Fang, Guanqi
AU - Pan, Rong
N1 - Funding Information:
This research is supported by the National Natural Science Foundation of China (Grant No. 71801171).
Publisher Copyright:
© ESREL 2020-PSAM15 Organizers. Published by Research Publishing, Singapore.
PY - 2020
Y1 - 2020
N2 - This article proposes a reliability model for systems subject to dependent degradation and external shocks. The dependence between degradation and external shocks is considered as follows. When the system is working but the degradation level reaches a critical threshold, the degradation rate increases in a stochastic sense. Meanwhile, the system becomes more vulnerable to external shocks due to accumulated degradation. An extended degradationthreshold-shock (DTS) model is developed to describe these two competing but dependent failure processes. The continuous degradation path is monotone and modeled by a two-stage inverse Gaussian (IG) process with random effects to account for the unit-specific heterogeneity across systems. External shocks arrive at the system following a doubly stochastic Poisson process (DSPP) with stochastic increasing intensity which depends on the degradation level. Integrating the degradation-based and shock-based failure processes, the system reliability function is derived. Afterwards, a numerical example is presented to illustrate the applicability of the developed reliability model, along with sensitivity analysis to examine the effect of several parameters on the reliability performance. The proposed reliability model is supposed to be applied directly or customized for other complex systems that experience dependent competing failure processes.
AB - This article proposes a reliability model for systems subject to dependent degradation and external shocks. The dependence between degradation and external shocks is considered as follows. When the system is working but the degradation level reaches a critical threshold, the degradation rate increases in a stochastic sense. Meanwhile, the system becomes more vulnerable to external shocks due to accumulated degradation. An extended degradationthreshold-shock (DTS) model is developed to describe these two competing but dependent failure processes. The continuous degradation path is monotone and modeled by a two-stage inverse Gaussian (IG) process with random effects to account for the unit-specific heterogeneity across systems. External shocks arrive at the system following a doubly stochastic Poisson process (DSPP) with stochastic increasing intensity which depends on the degradation level. Integrating the degradation-based and shock-based failure processes, the system reliability function is derived. Afterwards, a numerical example is presented to illustrate the applicability of the developed reliability model, along with sensitivity analysis to examine the effect of several parameters on the reliability performance. The proposed reliability model is supposed to be applied directly or customized for other complex systems that experience dependent competing failure processes.
KW - Degradation
KW - Dependent competing failure processes
KW - Doubly stochastic Poisson process
KW - Inverse Gaussian process
KW - Reliability modeling
KW - Shocks
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U2 - 10.3850/978-981-14-8593-0_3720-cd
DO - 10.3850/978-981-14-8593-0_3720-cd
M3 - Conference contribution
AN - SCOPUS:85107295125
SN - 9789811485930
T3 - Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference
SP - 2073
EP - 2078
BT - Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference
A2 - Baraldi, Piero
A2 - Di Maio, Francesco
A2 - Zio, Enrico
PB - Research Publishing, Singapore
T2 - 30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM15 2020
Y2 - 1 November 2020 through 5 November 2020
ER -