Overhaul planning and exchange scheduling for maintenance services with rotable inventory and limited processing capacity

We introduce a mathematical model with integrality property for maintenance and component exchange scheduling.The objective is to minimize total earliness for exchanges of rotable components.We propose an exact solution algorithm for the problem.A case study from the airline MRO industry is used to illustrate our methodology. Maintenance, repair and overhauling (MRO) of high cost equipment used in many industries are typically subject to regulations set by local governments or international agencies. For example in the aviation industry, critical equipment must be overhauled at certain intervals for continuing permission of use. As such, the overhaul must be completed by strict deadlines. Since the overhaul is typically a long process, MRO companies may implement exchange programs where they carry so called rotable inventory for exchanging expensive modules that require overhaul so that the equipment can continue its services with minimal interruption. The extracted module is overhauled in a capacitated facility and rotated back to the inventory for a future exchange. Since both the rotable inventory and the overhaul process capacity are limited, it may be necessary to carry out some of the exchanges earlier than their deadlines. Early exchanges results in a decrease in the maintenance cycle time of the equipment, which is not desirable for the equipment user. In this paper, we propose an integer programming model so as to minimize total earliness by generating optimal overhaul start times for rotables on parallel processing lines and exchange timetables for orders. We show that the LP relaxation of the proposed model has the integrality property. We develop a practical exact solution algorithm for the model based on a full-delay scheduling approach with backward allocation. The proposed procedure is demonstrated through both a numerical study and a case study from the airline MRO service industry.