Identification of strategic maintenance resource demand: A reliability based approach

Airline Maintenance and Engineering (M&E) organizations are faced with a number of repairs time to time for their fleet of aircraft due to accidental damages. As these damages are unpredictable in nature, the approach to repairing these damages is reactive. These type of repairs fall under the category of corrective or unscheduled maintenance policy compared to the planned preventive or scheduled maintenance. As the occurrence of these unscheduled repairs result in consumption of more maintenance resources in an untimely manner, they add to the existing costs for the organisation. Hence, it is of interest to the M&E to predict the demand for these resources for a future period so that the organisation is better prepared to handle future maintenance activities. One of the resources impacted due to unscheduled repairs is capacity, i.e maintenance hangar facility. If the capacity of a hangar facility can be divided into certain number of slots, then prediction of the demand for these slots would be beneficial to the maintenance planner. In order to identify the demand for these slots, it is first important to forecast the trend of unscheduled repairs. To achieve this goal, i.e. prediction of future repair and determination of slot capacity, a novel application for the integrated use of a reliability and inventory control model has been identified in this thesis. Here, the concepts of inventory control has been specifically applied to a maintenance application to determine the maintenance capacity by taking into account the stochastic demand of unscheduled repairs. The model used to predict the demand of unscheduled repair is a Non-homogeneous Poisson Process (NHPP) reliability model with a Power law intensity function and the inventory control model that was found to be applicable is the singlesystem single location Base-stock policy model. The reliability model considers the superpositioning principle through which the failure behaviour for the entire fleet of aircraft could be predicted. Certain performance measures were identified from the inventory control model, which helped in determining capacity based on optimum costs as well as service level requirements. As a proof of concept, a study is done on identifying the long-run capacity requirements for a fleet of Boeing 777 aircraft of a major European airline. Two specific structural components were identified on which the study was carried out, namely, the leading slats and the outboard flaps. The results showed the successful implementation of the model by identifying 30 slots necessary in the next 1500 flight cycles at an optimum cost for the case of leading edge slats.Aerospace Engineerin