Survival signature based robust redundancy allocation under imprecise probability

Chunyan Ling, Lechang Yang, Kaixuan Feng and Way Kuo

Reliability Engineering and System Safety, 2023, vol. 239, issue C

Abstract: his paper investigates the robust reliability design of a complex system with imprecise model parameters. The considered system is supposed to have multiple types of components. The random failure times of different types of components are independently distributed, while the i.i.d. assumption holds for failure times of components of the same type. The challenge lies in the involvement of imprecise parameters in the decision-making, which makes the redundancy allocation problem (RAP) increasingly complex as the injection of uncertainty. To address this gap, an efficient system reliability analysis method based on the survival signature is employed, in order to take its advantage of separating the probabilistic information from the embedded structural information. To facilitate the decision-making, a robust counterpart of RAP is constructed by using the min-max regret framework. After that, the corresponding min-max optimization problem is first decomposed into several subproblems, and then solved in an iterative way. The superiority of the proposed method is demonstrated and validated by several case studies.

Keywords: Robust reliability design; Imprecise model parameters; Random failure time; Redundancy allocation; Survival signature (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:239:y:2023:i:c:s0951832023004246

DOI: 10.1016/j.ress.2023.109510

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