An optimizing maintenance policy for airborne redundant systems operating with faults by using Markov process and NSGA-II

Redundancy is widely applied in modern airborne systems. Operation with faults in redundant airborne systems can improve the dispatch reliability of aircraft and reduce operational losses due to flight delays or cancellations. In this paper, a Markov model of redundant airborne systems operating with faults is developed, and an analytical method for state frequency calculation is proposed based on the Markov process. On this basis, the multiobjective optimization model is built by taking the time intervals of systems operating with faults as the decision variables, the average safety requirement as the constraint, and the operation cost and dispatch reliability as objectives. Then an algorithm based on NSGA-II is proposed to solve the multiobjective optimization model. Finally, a case study is given to illustrate the application of our proposed method. The results and discussions show that our method has advantages in both accuracy and efficiency compared with some present approaches. Additionally, the loss caused by flight delays and cancellations can be controlled by selecting the proper time intervals optimized by our method. In this way, the operating cost and dispatch reliability can be optimized by airlines, and aircraft safety can be ensured.