Reliability and Availability Analysis of a Repairable $k$-out-of-$n:G$ System With $R$ Repairmen Subject to Shut-Off Rules

Moghaddass, Ramin; Zuo, Ming J.; Qu, Jian

doi:10.1109/tr.2011.2161703

Cited by 50 publications

(13 citation statements)

References 20 publications

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“…Moghaddass et al [24] did the reliability and availability analysis of a repairable -out-of-: system with repairmen subject to shut-off rules. Wang and Pham [29] studied a multi-objective maintenance optimization for one single-unit system subject to the dependent competing risks of degradation wear and random shocks.…”

Section: Notationmentioning

confidence: 99%

Multi-Point and Multi-Interval Availabilities

Cui

Liu

2013

IEEE Trans. Rel.

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Availability is an important measure of performance for repairable systems because it can describe the probability of a repairable system being in working states. Single point and interval availability measurements (availabilities) have been widely used, but they cannot meet the requirements of all applications. In this paper, multi-point, multi-interval, and mixed multi-pointinterval availabilities are introduced, which are extensions of the single point and interval availabilities. The multi-interval availability formula was given by Csenki in 2007 by using the induction method in which the multi-interval availability was called the joint interval reliability, but a new simple technique is provided to present the formula of multi-interval availability in this paper. We also consider the steady-state situations for all new availabilities. For Markov repairable systems, the calculation formulae are presented for the new availabilities, and some properties of new availabilities are discussed too. Finally, some special cases and numerical examples are given to illustrate the results obtained in the paper.Index Terms-Interval availability, joint interval reliability, Markov repairable system, mixed multi-point-interval availability, multi-interval availability, multi-point availability.

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Section: Notationmentioning

confidence: 99%

Multi-Point and Multi-Interval Availabilities

Cui

Liu

2013

IEEE Trans. Rel.

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“…Digital communication networks have become essential to many diverse systems, such as computer and communication systems [1], distributed computing networks [2], [17], power electronic systems [3], oil/gas production systems [4], grid systems [5], repairable systems [6]- [8], human systems [9], the internet of things [10] and wireless sensor networks [11], etc [12]- [15]. All of these can be modeled as networks in system planning, design and control [1]- [13].…”

Section: Introductionmentioning

confidence: 99%

A Novel Convolution-Based Algorithm for the Acyclic Network Symbolic Reliability Function Problem

Zhang

Yeh

et al. 2020

IEEE Access

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Acyclic (binary-state) networks are commonly implemented in many diverse disciplines and applications, including information systems, processes management, project management. These networks owe their popularity to the fact that they do not use directed cycles. Network reliability is the most commonly used tool for evaluating and managing systems modeled on acyclic networks, and minimal paths (MPs) play a significant role in evaluating this reliability. This study therefore proposes a new algorithm based on a novel convolution concept for evaluating acyclic network reliability. The proposed algorithm is able to find all convolution-based MP sets within polynomial time, and then obtain the symbolic function of the acyclic network reliability in terms of those convolution-based MP sets based on the pivotal decomposition. Its total time complexity is O(2 n), which is the best among all existing MP algorithms which are at least O(2 |P|), where O(|P|) = O(2 n), and n and |P| are the number of nodes and MPs, respectively. The correctness and time complexity of the proposed algorithm is proven and examined. An example is used to display the novel convolution-based algorithm is implemented to solve the acyclic network reliability problem.

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“…A typical form of redundancy is a -out-ofconfiguration in which at least out of components must work for normal operation of system. When using traditional methods [1][2][3][4] to analyze reliability of -out-of-system, independence is assumed within the system, which means that a component failure does not affect the failure rate or performance of surviving components. However, in the real world, many systems are load-sharing, such as electric generators sharing an electrical load in a power plant, cables in a suspension bridge, and valves or pumps in a hydraulic system.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of Load-SharingK-out-of-NSystem Considering Component Degradation

Yang

Zeng

Guo

2015

Mathematical Problems in Engineering

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The -out-of-configuration is a typical form of redundancy techniques to improve system reliability, where at least -out-ofcomponents must work for successful operation of system. When the components are degraded, more components are needed to meet the system requirement, which means that the value of has to increase. The current reliability analysis methods overestimate the reliability, because using constant ignores the degradation effect. In a load-sharing system with degrading components, the workload shared on each surviving component will increase after a random component failure, resulting in higher failure rate and increased performance degradation rate. This paper proposes a method combining a tampered failure rate model with a performance degradation model to analyze the reliability of load-sharing -out-of-system with degrading components. The proposed method considers the value of as a variable which is derived by the performance degradation model. Also, the loadsharing effect is evaluated by the tampered failure rate model. Monte-Carlo simulation procedure is used to estimate the discrete probability distribution of . The case of a solar panel is studied in this paper, and the result shows that the reliability considering component degradation is less than that ignoring component degradation.

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Reliability and Availability Analysis of a Repairable $k$-out-of-$n:G$ System With $R$ Repairmen Subject to Shut-Off Rules

Cited by 50 publications

References 20 publications

Multi-Point and Multi-Interval Availabilities

Multi-Point and Multi-Interval Availabilities

A Novel Convolution-Based Algorithm for the Acyclic Network Symbolic Reliability Function Problem

Reliability Analysis of Load-SharingK-out-of-NSystem Considering Component Degradation

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