Reliability evaluation of a k-out-of-n(G)-subsystem based multi-state system with common bus performance sharing

Su, Peng; Wang, Guanjun; Duan, Fengjun

doi:10.1016/j.ress.2020.106884

Cited by 39 publications

(12 citation statements)

References 34 publications

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“…Then, given η (z) as the probability distribution of transmission capacity C, we can obtain final system ŨA (z) expressing the probability distribution of performance excess and performance deficiency after performance sharing, which is consistent with equation (6.4). The form of the corresponding combination operator is (19), as shown at the bottom of the next page.…”

Section: Volume 10 2022mentioning

confidence: 99%

“…The reliability of the MSS is the probability of df = 0 ∩ ŝf = 0(the probability that both performance excess and performance deficiency are zero), namely, the coefficient qf of qf z 0;0 in the formula UGF (see Eq. 19).…”

Section: Volume 10 2022mentioning

confidence: 99%

“…In the systems of practice such as heating, integrated circuit, power grid, communication and production systems, the demand as well as the corresponding performance of each component are stochastic [12]- [16]. If the performance of a unit is surplus after meeting its own demand, the common bus can transmit the excess The associate editor coordinating the review of this manuscript and approving it for publication was Zhaojun Steven Li. performance to other units which cannot meet their demand by their own performances through, in order to improve the reliability of the system [17]- [19]. The stochastic capacity of the transmission system decides its performance that can be transmitted.…”

Section: Introductionmentioning

confidence: 99%

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Reliability Evaluation of Multi-State Systems With Common Bus Performance Sharing Considering Performance Excess

et al. 2022

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In a multi-state system with common bus performance sharing, the residual performance of any sub-unit can be shared to other sub-units with insufficient performance by the common bus with stochastic sharing capacity. This study extends the reliability evaluation model by considering both the minimum and maximum requirements of elements, which should not only meet the random minimum requirements of each single element, but also require that there should be no excess performance. The reliability of the multistate system (MSS) is estimated by using the Universal Generating Function (UGF) technique. Illustrative example is presented to illustrate the procedures. In addition, the genetic operator is used to obtain the optimal location of the components with maximum reliability.

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Section: Volume 10 2022mentioning

confidence: 99%

Section: Volume 10 2022mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reliability Evaluation of Multi-State Systems With Common Bus Performance Sharing Considering Performance Excess

et al. 2022

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“…The UGF technique is a method of representing the probability distribution of multi-state system performance, which is widely used in the research of reliability analysis and optimization of multi-state system [18][19][20][21][22]. The UGF is a polynomial used to represent the distribution of a discrete random variable.…”

Section: System Reliability Evaluation Modelmentioning

confidence: 99%

Multi-State System Reliability Evaluation and Component Allocation Optimization Under Multi-Level Performance Sharing

et al. 2021

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With the development of science and technology, the structure of engineering system has become increasingly large and complex. In order to ensure the safety and stability of the system in operation, the reliability evaluation of complex system has become an important research field. Based on the actual engineering system, this paper proposes a multi-state system with multi-level performance sharing mechanism. On this basis, we established a system reliability evaluation model using universal generating function technique. Through numerical examples, the application of the model and analyze the influence of different parameters on system reliability are demonstrated. In addition, we also use genetic algorithm to optimize the allocation of components in the system, so as to improve the reliability of the system. Different from the previous studies on system reliability with common bus performance sharing, the system proposed in this study is more general.

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“…6–9 Zhao et al 10 optimized the mission success probability of a PMS that consists of some subsystems in series. A PMS which consists of k -out-of- n (G)-subsystem was studied by Su et al 11 Furthermore, some other works have integrated different factors such as redundancy, performance sharing and multiple failure modes into PMSs. For example, a PMS with performance sharing mechanism was studied by Yu et al 12 PMSs with time redundancy, multiple failure modes and finite number of phase switches were also considered.…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of multi-state elements in a sliding window system with phased missions

Kou

Gao

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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Many real-world engineering systems such as aerospace systems, intelligent transportation systems and high-performance computing systems are designed to complete missions in multiple phases. These types of systems are known as phased-mission systems. Inspired by an industrial heating system, this research proposes a generalized linear sliding window system with phased missions. The proposed system consists of N nodes with M multi-state elements that are subject to degradation. The linear sliding window system fails if the cumulative performance of any r consecutive nodes is less than the pre-determined demand in any phase. The degradation process of each element is modeled by a continuous-time Markov chain. A novel reliability evaluation algorithm is proposed for the linear sliding window system with phased missions by extending the universal generating function technique. Furthermore, the optimal element allocation strategy is determined using the particle swarm optimization. The effectiveness of the proposed algorithm is confirmed by a set of numerical experiments.

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Reliability evaluation of a k-out-of-n(G)-subsystem based multi-state system with common bus performance sharing

Cited by 39 publications

References 34 publications

Reliability Evaluation of Multi-State Systems With Common Bus Performance Sharing Considering Performance Excess

Reliability Evaluation of Multi-State Systems With Common Bus Performance Sharing Considering Performance Excess

Multi-State System Reliability Evaluation and Component Allocation Optimization Under Multi-Level Performance Sharing

Optimal allocation of multi-state elements in a sliding window system with phased missions

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