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Reliability analysis of multi‐state series systems with performance sharing mechanism under epistemic uncertainty
Author(s) -
Qiu Siqi,
Ming Henry X. G.
Publication year - 2019
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2488
Subject(s) - reliability (semiconductor) , uncertainty quantification , computer science , interval (graph theory) , function (biology) , interval arithmetic , uncertainty analysis , series (stratigraphy) , reliability engineering , state (computer science) , mechanism (biology) , algorithm , mathematics , engineering , simulation , machine learning , mathematical analysis , paleontology , power (physics) , philosophy , physics , epistemology , quantum mechanics , combinatorics , evolutionary biology , bounded function , biology
Abstract For real engineering systems, it is sometimes difficult to obtain sufficient data to estimate the precise values of some parameters in reliability analysis. This kind of uncertainty is called epistemic uncertainty. Because of the epistemic uncertainty, traditional universal generating function (UGF) technique is not appropriate to analyze the reliability of systems with performance sharing mechanism under epistemic uncertainty. This paper proposes a belief UGF (BUGF)‐based method to evaluate the reliability of multi‐state series systems with performance sharing mechanism under epistemic uncertainty. The proposed BUGF‐based reliability analysis method is validated by an illustrative example and compared with the interval UGF (IUGF)‐based methods with interval arithmetic or affine arithmetic. The illustrative example shows that the proposed BUGF‐based method is more efficient than the IUGF‐based methods in the reliability analysis of multi‐state systems (MSSs) with performance sharing mechanism under epistemic uncertainty.