A two-stage optimization approach for aircraft hangar maintenance planning and staff assignment problems under MRO outsourcing mode

Abstract

Aircraft Maintenance Repair and Overhaul (MRO) is essential to ensure aviation safety and air transport operations. An aircraft has to temporally suspend its service and receive extensive maintenance in the hangar upon reaching the prescribed flying hours and take-off/landing times. Traditionally, each airline company undertakes hangar maintenance for its own fleet, however the nature of MRO operations has changed with the rapid development of air transport demand. Outsourcing hangar maintenance to maintenance service companies has been increasing among airlines, enabling airlines to reduce the cost of MRO while meeting the aircraft’s safety requirements. After receiving the maintenance order with specifications, the maintenance service company needs to determine the maintenance schedules, parking stand allocation, aircraft movement path and staff assignment in the integrated planning problem. To integrate the abovementioned factors, a Mixed-Integer Linear Programming (MILP) model is developed. In the MILP model, geometric factors are considered, which are integrated with the multi-skill manpower assignment afterwards. Consideration of staff with multiple types of maintenance skills, aligning with the practice of sophisticated hangar maintenance, is incorporated in the model. Secondly, given the complexity of the integrated problem, a two-stage optimization approach is developed by decomposing the original model, which is coordinated by the linkage constraints between the geometric and numeric decision-making scattering in the decomposed subproblems. The results and analysis of numerical experimentation are reported, which shows: (i) the adaptability and efficiency of the two-stage optimization approach and (ii) the tractability of the two-stage optimization approach, which manage to produce good quality solutions in solving medium- to large- size instances. The impacts of maintenance demand intensity and manpower supply variation are also analysed to provide managerial insights.