A decision diagram based reliability evaluation method for multiple phased-mission systems

Zhang, Shuai; Sun, Shudong; Si, Shubin; Wang, Peng

doi:10.17531/ein.2017.3.20

Cited by 10 publications

(5 citation statements)

References 25 publications

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“…However, to adapt to our situation, the MDD used is somewhat different as in most papers. In most papers using MDD, each node in the MDD corresponds to a system element, each branch corresponds to a state of the element, and therefore each path leading to system success represents the set of elements that have failed and the set of elements that have not failed [15,28]. In our case, if the traditional MDD is used, for each path representing system success, one still needs to enumerate all the possible sequence of the system failures.…”

Section: The Modelmentioning

confidence: 99%

Reliability of interdependent networks with cascading failures

Peng

2018

Eksploatacja i Niezawodność – Maintenance and Reliability

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The reliability of network systems of various structures has been studied by many researchers. However, most of the works just consider the reliability of a single network system. In practice, different networks may be interdependent such that the failure in one network may result in the failure in another network. The cascading failures have been shown to be catastrophic by some researchers. However, the quantitative evaluation for the reliability of interdependent networks has not been proposed. In this paper, a multi-valued decision diagram based approach is presented to evaluate the reliability of interdependent networks. Illustrative examples are proposed to demonstrate the application of the framework.

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Section: The Modelmentioning

confidence: 99%

Reliability of interdependent networks with cascading failures

Peng

2018

Eksploatacja i Niezawodność – Maintenance and Reliability

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“…2 For example, recursive methods were widely applied to calculate the reliability of PMSs with relatively simple structures. 19–21 When PMSs become more complex, some non-simulation methods such as the binary decision diagram (BDD), 22,23 the multivalued decision diagram (MDD) 24,25 and the multiple-terminal binary decision diagram (MTBDD) 26 are used to evaluate the reliability of these PMSs. However, these methods can only handle PMSs with statistical independent elements.…”

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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“…Basically, existing methodologies can be categorized into the simulation and the analytical methods. The simulation methods are outstanding in their wide applicability to a variety of scenarios [23,28]; whereas the analytical methods, including binary decision diagram (BDD)-based method [17,24,25], multivalued decision diagram (MDD)-based method [13,16], Markov chains-based method [18], Markov reward model-universal generating function (UGF) technique [7], Bayesian networks approach [4], recursive algorithm [3], have advantages in obtaining accurate results with high efficiency, but may not be suitable in large-scale PMS with complex dynamic behaviors.…”

Section: Introductionmentioning

confidence: 99%