Multi-objective optimization of reliability-redundancy allocation problem for multi-type production systems considering redundancy strategies

Wei Wang, Mingqiang Lin, Yongnian Fu, Xiaoping Luo and Hanghang Chen

Reliability Engineering and System Safety, 2020, vol. 193, issue C

Abstract: This paper innovatively proposes a new model of multi-type production system which can process different types of production. The multi-type production system consists of several independent sequentially ordered subsystems which undertaking different tasks. Different types of production require different manufacturing lines: required subsystems will be powered on, while others powered off. The system can switch into different production line based on detection results. A binary matrix is suggested to describe the composition of each production line of the multi-type production system. Reliability-redundancy allocation on each subsystem is considered for achieving higher reliabilities of different production lines. The reliability-redundancy allocation problem for the proposed multi-type production system is essentially multi-objective subject to resource constraints. This paper formulates the multi-objective optimization problem and considers the optimal redundancy strategy, either active or cold standby. The exact reliabilities of cold standby redundant subsystems with imperfect detector/switch are determined by introducing an approach based on continuous time Markov chain. Then, a multi-objective evolutionary algorithm is suggested to solve the proposed reliability-redundancy allocation problem. Finally, numerical examples are presented to illustrate the proposed methods.

Keywords: Multi-type production system; Structure matrix; Reliability-redundancy allocation; Redundancy strategy; Multi-objective optimization; NSGA-II (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:193:y:2020:i:c:s095183201930287x

DOI: 10.1016/j.ress.2019.106681

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