Dynamic Adjustment of Long-Term Maintenance Plan Based on Gray Wolf Optimizer

Abstract

Aeroengine is an expensive large-scale precision and complex equipment, in the operation process needs to be repaired and maintained many times. The current management of civil aeroengine is generally aeroengine fleet as a unit, the development of maintenance plans, but once the maintenance plan is determined, if encountered unplanned disturbances, such as aeroengine repair ahead of schedule and other emergencies, the maintenance plan cannot make self-adjustment, it is difficult to be applied to the engineering practice. In view of the above problems, this paper proposes and establishes a dynamic adjustment model for long-term fleet maintenance plan by considering the actual needs of engineering and combining with the research on dynamic scheduling. In this model, the optimization goal is to minimize the cost generated by engine shortage and engine waste, minimize the balanced index of repair delivery, and minimize the difference between the plans before and after dynamic adjustment. Using the gray wolf optimization algorithm (GWO) for solving, the dynamic adjustment model is compared with the nondynamic adjustment model in a comparative test, and the accuracy and practicality of the dynamic adjustment model are verified.