Abstract
This paper presents a Reinforcement Learning (RL) approach to optimize the long-term scheduling of maintenance for an aircraft fleet. The problem considers fleet status, maintenance capacity, and other maintenance constraints to schedule hangar checks for a specified time horizon. The checks are scheduled within an interval, and the goal is to, schedule them as close as possible to their due date. In doing so, the number of checks is reduced, and the fleet availability increases. A Deep Q-learning algorithm is used to optimize the scheduling policy. The model is validated in a real scenario using maintenance data from 45 aircraft. The maintenance plan that is generated with our approach is compared with a previous study, which presented a Dynamic Programming (DP) based approach and airline estimations for the same period. The results show a reduction in the number of checks scheduled, which indicates the potential of RL in solving this problem. The adaptability of RL is also tested by introducing small disturbances in the initial conditions. After training the model with these simulated scenarios, the results show the robustness of the RL approach and its ability to generate efficient maintenance plans in only a few seconds.
Highlights
IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
The number of A and C-checks scheduled during the entire horizon, the average flight hours (FH) used between two consecutive A and C-checks, the number of A and C-checks scheduled using the tolerance, and the number of A-checks merged into C-checks
The results indicate an improvement of both the Dynamic Programming (DP) and the Reinforcement Learning (RL) approaches over the airline in all of the KPI considered, meaning that both methods can generate a better maintenance plan much faster
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Aircraft maintenance is the repair, modification, overhaul, inspection, and determination of the condition of aircraft systems, components, and structures that aims at providing aircraft airworthiness for operations [1]
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