Maintenance Optimization of Consecutive-$k$-out-of-$n$ System with Multiobjective Birnbaum Importance-based Particle Swarm Optimization

Abstract

This paper focuses on the maintenance optimization problem of consecutive-k-out-of-n systems which are maintained through exchanging the position of components and improving the reliability of components. At first, the multi-objective maintenance optimization model is constructed based on comprehensive consideration of the system reliability and maintenance cost. Then, the relationship between component reliability and maintenance cost is discussed and introduced into the Birnbaum importance to establish the idea of multi-objective Birnbaum importance (MOBI). It is clear that the maintenance strategy based on MOBI was more effective than the maintenance strategy based on traditional Birnbaum importance. Thirdly, the MOBI-based particle swarm optimization (MOBI-PSO) method is proposed by taking the advantages of MOBI and particle swarm optimization. Finally, the MOBI-PSO is applied to solve the problem of multi-objective maintenance optimization for consecutive-k-out-of-n systems. The simulation results show that the optimization algorithm based on MOBI could make the system more reliable with lower maintenance cost after maintenance.