Maintenance optimization of reconfigurable systems based on multi-objective Birnbaum importance

Abstract

Reconfigurable systems can meet the changing requirements of system performance by several approaches, such as adjusting the system structure, improving the component performance, and reassigning components. However, it is also challengeable to find a cost-effective maintenance scheme by integrating these maintenance approaches. This article investigates the multi-objective maintenance optimization problem for reconfigurable systems with the consideration of maintenance cost and system reliability. First, the multi-objective maintenance optimization model is established to maximize the system reliability and minimize the total maintenance cost considering the constraints on budget and system performance. Second, a multi-objective Birnbaum importance is proposed to quantify the contribution of the individual component to the system reliability. The multi-objective Birnbaum importance–based non-dominated sorting genetic algorithm II is developed to obtain the optimal maintenance scheme with the maximum system reliability and minimum maintenance cost. Finally, the performance of multi-objective Birnbaum importance–based non-dominated sorting genetic algorithm II is proved by three numerical experiments. Experiment 1 verifies the advantage of multi-objective Birnbaum importance compared with Birnbaum importance to improve the system reliability in direct maintenance. Experiment 2 shows that the effectiveness of multi-objective Birnbaum importance is much better than that of the Birnbaum importance to enhance the performance of non-dominated sorting genetic algorithm II in comprehensive maintenance. Experiment 3 illustrates that the performance of multi-objective Birnbaum importance–based non-dominated sorting genetic algorithm II is better than that of other multi-objective algorithms combining with multi-objective Birnbaum importance.