Multi-objective optimization of reliability-redundancy allocation problem for multi-type production systems considering redundancy strategies - Wang, Wei; Lin, Mingqiang; Fu, Yongnian; Luo, Xiaoping; Chen, Hanghang (Reliability engineering & system safety, 2020)
•A new model of multi-type production systems that generalizes the manufacturing systems with multiple switchable production lines is developed.•A binary matrix is used to describe the composition of each production line of the multi-type production system.•RRAP considering redundancy strategies (either active or cold standby) is modeled for enhancing the reliabilities of different production lines.•A NSGA-II is developed to solve the RRAP for the multi-type production system. 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.