Belief reliability analysis of competing for failure systems with bi-uncertain variables

Shi, Haiyan; Wei, Chun; Zhang, Zhiqiang; Liu, Baoliang; Wen, Yanqing

doi:10.1007/s12652-020-02878-z

Cited by 11 publications

(3 citation statements)

References 33 publications

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“…Series systems [13,78,81,84,[98][99][100][101], parallel systems [13,81,84,[98][99][100][101], series-parallel hybrid systems [81,[99][100][101][102], cold standby systems [99,101,[103][104][105], warm standby systems [103], k-out-of-n systems [84,100,106-109], bridge systems [85,110], general configurations and algorithms [78,81,100,110] Fault tree analysis Minimal cut set theorem [13,84], analysis algorithm [84] Importance index Uncertain system [108,111], uncertain random system [112] Belief reliability analysis of systems with degradation-shock dependency Uncertain degradation with random shock arrival time and uncertain shock size [113,114], uncertain degradation with uncertain shock [115][116][117][118], degradation-shock dependency with a change point …”

Section: Methodsmentioning

confidence: 99%

Belief Reliability: A Scientific Exploration of Reliability Engineering

Zhang,

Li,

et al. 2024

J. of Syst. Eng. Electron.

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This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability. Beginning with the origin of reliability engineering, the problems of present theories for reliability engineering are summarized as a query, a dilemma, and a puzzle. Then, through philosophical reflection, we introduce the theoretical solutions given by belief reliability theory, including scientific principles, basic equations, reliability science experiments, and mathematical measures. The basic methods and technologies of belief reliability, namely, belief reliability analysis, function-oriented belief reliability design, belief reliability evaluation, and several newly developed methods and technologies are sequentially elaborated and overviewed. Based on the above investigations, we summarize the significance of belief reliability theory and make some prospects about future research, aiming to promote the development of reliability science and engineering.

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Section: Methodsmentioning

confidence: 99%

Belief Reliability: A Scientific Exploration of Reliability Engineering

Zhang,

Li,

et al. 2024

J. of Syst. Eng. Electron.

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“…developed a travel time belief reliability that incorporated the influences of epistemic and random uncertainties on reliability to measure the travel time reliability of urban road networks. The belief reliability function and the mean time to failure of micro‐electromechanical systems was studied by Shi et al 74 . Kang et al 75 .…”

Section: The Latest Developments In Reliability Analysis For Complex ...mentioning

confidence: 99%

“…Yang et al 73 developed a travel time belief reliability that incorporated the influences of epistemic and random uncertainties on reliability to measure the travel time reliability of urban road networks. The belief reliability function and the mean time to failure of micro-electromechanical systems was studied by Shi et al 74 Kang et al 75 reviewed non-probabilistic reliability measurements, such as evidence theory-based metrics, interval-based metrics, fuzzy-based metrics, possibility-based metrics, and belief reliability, under epistemic uncertainty and showed that belief reliability was a promising reliability metric for measuring reliability affected by epistemic uncertainty, but their research on belief reliability was far from mature.…”

Section: Non-strict Probabilistic Metrics-based Ramentioning

confidence: 99%

Reliability analysis of complex electromechanical systems: State of the art, challenges, and prospects

Wang

Zhang

et al. 2022

Quality & Reliability Eng

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As the core foundation of reliability engineering and one of the most crucial aspects of general quality, reliability has been attracting increasing attention from industry and academia. Numerous publications on reliability analysis (RA) have appeared in academic journals, conference proceedings, and technical reports. However, there has not been a systematic summary that covers RA data, models, methods, indicators, and software comprehensively. To fill this gap, this paper analyzed the challenges and the state of the art, as well as determined the future prospects for research on RA. This paper introduces the features of modern complex electromechanical systems (CES), then summarizes the current challenges to the RA of CES. Next, it reviews the latest developments, such as reliability theories, models, methods, and software, then summarizes and compares their advantages and limitations. Finally, it discusses future prospects from the perspectives of reliability data, modeling, decoupling, evaluation indicators, and timely prediction. It is expected that this paper would serve as an introduction to RA for researchers new to this field and as a summary of the current frontiers of RA for experienced researchers.

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Reliability assessment with uncertain thresholds considering degradation and shock

Wei,

Shi,

Zhang

et al. 2023

Soft Comput

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There are often many reasons for equipment failure. When the performance of a certain aspect drops to a certain threshold, the equipment will fail. Affected by other factors, the threshold is uncertain. A reliability model of uncertain thresholds where degradation and external shocks compete with each other is established, and the reliability of the model are evaluated according to uncertainty theory. Under three different shock types, the reliability of the equipment is obtained. The reliability with uncertain thresholds and the reliability with constants thresholds are compared. The results show that in different periods of equipment operation, the reliability of the uncertain thresholds is different with the reliability of the constants thresholds. If the threshold is simply regarded as a known constant, it will cause inaccuracies in the reliability assessment of the system, and miss the best maintenance time, causing unnecessary losses. Taking the microelectronic mechanical system as an example, the superiority of the proposed model is illustrated.

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Belief reliability analysis of competing for failure systems with bi-uncertain variables

Cited by 11 publications

References 33 publications

Belief Reliability: A Scientific Exploration of Reliability Engineering

Belief Reliability: A Scientific Exploration of Reliability Engineering

Reliability analysis of complex electromechanical systems: State of the art, challenges, and prospects

Reliability assessment with uncertain thresholds considering degradation and shock

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