Reliability modeling of modular k-out-of-n systems with functional dependency: A case study of radar transmitter systems

Tangfan Xiahou, Yi-Xuan Zheng, Yu Liu and Hong Chen

Reliability Engineering and System Safety, 2023, vol. 233, issue C

Abstract: The k-out-of-n systems are among the most important redundancy structures in engineering practices, and their reliability assessment has been extensively studied in the past decades. However, components in a k-out-of-n structure are often subject to functional dependency (FDEP), in which component states are affected by other components’ states in the system. In this article, we study a new system structure, namely modular k-out-of-n system with FDEP. In such a system, the failure of some specific components will disable some components in the k-out-of-n structure. Bayesian network (BN) models are used to construct the structure function of modular k-out-of-n systems. The parameters encoded in the graphical structure of the modular k-out-of-n system are automatically generated by a customized algorithm. Furthermore, a dynamic BN (DBN) is developed to update the reliability of modular k-out-of-n system dynamically when observation data are collected from either component or system level. The Birnbaum importance measure of the different types of components in the modular k-out-of-n system is also evaluated by the DBN model via inserting evidence of the components’ states overtime. A real-world case of a radar transmitter system in the space launch site is studied to demonstrate the effectiveness of the proposed method.

Keywords: Modular k-out-of-n system; Functional dependency; Dynamic Bayesian network; Reliability modeling; Radar transmitter system (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:233:y:2023:i:c:s0951832023000352

DOI: 10.1016/j.ress.2023.109120

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