Reliability analysis and optimization of equal load-sharing k-out-of-n phased-mission systems

Chen, Jiakai; He, Yong; Wei, Wei

doi:10.17531/ein.2015.2.12

Cited by 10 publications

(7 citation statements)

References 31 publications

(50 reference statements)

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“…For example, the space and environmental conditions of some components in the system are generally the same, coupled with human factors such as design principle and actual operation, leading to dependency among components. In the most of existing researches on the system reliability modeling on dependent components, the correlations are known, such as load sharing, 28 cascading failure, 29 or common cause failure 30 . However, most of these correlations are not clear before system modeling.…”

Section: Introductionmentioning

confidence: 99%

A copula‐based reliability model for phased mission systems with dependent components

Zhan

Xiong

et al. 2023

Quality & Reliability Eng

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Recently, researches on the reliability analysis of phased mission systems (PMSs) are very popular. And most of the existing research on PMSs assumed that all the components are statistically independent on each other, which is not meet the engineering reality. The system structure changes from phase to phase in the PMSs, so the dependency among components may also change in different phases. Meanwhile, the well‐known phase dependency is also existing in the system reliability modeling. To model the varying dependency among components and phase dependency at the same time, a copula‐based method is proposed for the reliability analysis of PMS with correlated components. Firstly, the system reliability of multi‐state PMS with dependent components is evaluated by different copula functions. Then, multiple indicators are used to select the optimal copula functions for different phases. And an engineering case is illustrated to show the proposed copula‐based method.

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Section: Introductionmentioning

confidence: 99%

A copula‐based reliability model for phased mission systems with dependent components

Zhan

Xiong

et al. 2023

Quality & Reliability Eng

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“…Moreover, since the failure rates are dependent on the number of operating components, the components are allowed to be load-sharing when the standby components are hot. 28 In addition, we assume that the component lifetimes are independent in a given fixed phase of the mission. This implies that the component lifetimes are statistically dependent only via the common mission process since the component lifetimes are dependent on the phases of the mission.…”

Section: System Descriptionmentioning

confidence: 99%

“…There is an active line of research which focuses on phased-mission k -out-of- n systems in the literature. 25–34 Most of these papers 25–30 analyze the reliability and/or maintenance of the system assuming either deterministic phase sequence or deterministic phase durations. Amari 31 and Amari et al 32 propose hybrid analytic-simulation methods to compute the probability of completing phased missions with random phase durations and sequence.…”

Section: Introductionmentioning

confidence: 99%

Reliability of mission-based k-out-of-n systems with exponential phase durations and component lifetimes

Çekyay

2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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This paper focuses on the reliability analysis of [Formula: see text]-out-of-[Formula: see text] systems which are designed to perform a given mission consisting of several distinct phases. As the phases of the mission change, the reliability characteristics of the system and the system structure vary accordingly. The phase transition probabilities, phase durations, and component failure rates are dependent on the number of operating components. Moreover, the system is allowed to have cold, warm, or hot standby components. We propose computationally tractable methods to compute the system reliability, mean time to failure, and long-run availability for such a general system structure. We also provide a numerical analysis to show the applicability and the empirical computational complexity of the proposed methods.

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“…A common feature in a load-sharing system is that the workload is shared equally or unequally by the surviving components, and when a component fails, its load is distributed to the working components [32]. The increased workload on the component strongly affect its degradation rate and failure rate [11], which has been proved by many empirical studies of mechanical systems [7,26], and battery systems [20]. Therefore, due to load-sharing characteristics, the components are stochastically dependent on each other.…”

Section: Introductionmentioning

confidence: 99%

A reliability model for load-sharing k-out-of-n systems subject to soft and hard failures with dependent workload and shock effects

Che¹,

Zeng²,

Guo³

2020

Eksploatacja i Niezawodność – Maintenance and Reliability

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A reliAbility model for loAd-shAring k-out-of-n systems subject to soft And hArd fAilures with dependent workloAd And shock effects model niezAwodności dlA systemów typu k-z-n z podziAłem obciążeniA podlegAjących uszkodzeniom pArAmetrycznym i kAtAstroficznym, w których zAchodzi zAleżność między obciążeniem prAcą A skutkAmi obciążeń losowych A component in a k-out-of-n system may experience soft and hard failures resulting from exposure to natural degradation and random shocks. Due to load-sharing characteristics, once a component fails, the surviving components share an increased workload, which increases their own degradation rates. Moreover, under the larger workload, random shocks may cause larger abrupt degradation increments and larger shock sizes. Therefore, the system experiences the dependent workload and shock effects (DWSEs). Such dependence will cause the load-sharing system to fail more easily, though it is often not considered in existing methods. In this paper, to evaluate the system reliability more accurately, we develop a novel reliability model for load-sharing k-out-of-n systems with DWSEs. In the model, the joint probability density function of shock effects to soft and hard failures is developed to describe the DWSEs on a component. To derive an analytical expression of system reliability with load-sharing characteristics and DWSEs, conditional probability density function is used to model the random component failure times. A load-sharing Micro-Electro-Mechanical System (MEMS) is then utilized to illustrate the effectiveness of the reliability model.

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Reliability analysis and optimization of equal load-sharing k-out-of-n phased-mission systems

Cited by 10 publications

References 31 publications

A copula‐based reliability model for phased mission systems with dependent components

A copula‐based reliability model for phased mission systems with dependent components

Reliability of mission-based k-out-of-n systems with exponential phase durations and component lifetimes

A reliability model for load-sharing k-out-of-n systems subject to soft and hard failures with dependent workload and shock effects

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