Exchange Scheduling with Rotable Inventory in Maintenance-Repair-Overhaul Operations and Preventive Maintenance Planning

Abstract

An airplane is not deemed operable if any of its modules surpasses its scheduled overhaul deadline, according to regulations. To prevent downtime due to long processing times, airlines and maintenance-repair-overhaul (MRO) companies may participate in exchange programs that allow an airline to get an already-overhauled module from the MRO company's ready-to-use inventory in real time. In this setting, the inbound rotable module from the airline is overhauled and then rotated back to the ready-to-use inventory. Although exchange orders and their deadlines may be known at the start of the planning horizon, it may be necessary for the MRO company to undertake module exchange before these deadlines and suffer penalties due to capacity limits and inventory expenses. Furthermore, exchange items may not always be of equal quality and age, necessitating further transfer fees between the MRO service provider and the consumer to close the gap. Under such conditions, we address the joint problem of overhaul planning and exchange scheduling from the MRO company’s perspective. We propose a mixed integer linear programming model that seeks to minimize the total earliness, switching, procurement, and inventory costs. We introduce a redundant constraint to the model to enhance computational performance by speeding up the search for the optimal solution. We carry out a thorough numerical analysis to investigate the computational performance of the proposed model and gain managerial insights into the impact of key parameters on the optimal scheduling and inventory decisions. In addition to the MRO scheduling problem above, we address the cyclic preventive maintenance scheduling problem. A mixed integer linear programming model is provided with the objective function of minimizing the costs of scheduling the maintenance activities for a set of machines given several constraints on the frequency and order of the activities. We present a heuristic to solve the problem and conduct a numerical analysis to assess the performance of the heuristic and to investigate the impact of key parameters on the quality of the schedules.