Condition-based maintenance is an emerging maintenance strategy for aircraft, leveraging the constant collection of sensor information to facilitate diagnostics and prognostics of potential failures. The implementation of this strategy requires a significant initial investment and therefore, the resulting benefits should be quantified in advance. The objective of this research is to investigate the potential benefits of condition- based maintenance (CBM), and more specifically, the use of Prognostic & Health Management (PHM) systems operating with dynamic failure thresholds, with a focus on the required performance levels of the PHM systems. In this paper, a scheduling framework has been developed to schedule preventive maintenance tasks under application of prognostics, using a rolling-horizon scheduling approach to allocate tasks to appropriate maintenance blocks. The resulting maintenance schedule of a fleet of aircraft is subsequently used for the simulation of subsystem failures and the application of prognostics in order to anticipate them. Finally, the possibility of reducing maintenance cost, increasing fleet availability and improving operational reliability is investigated through a cost-benefit analysis. Results show significant improvements in terms of fleet availability and operational reliability, and minor reductions of maintenance cost. Moreover, the achieved benefits are shown to be in relation to the prognostic performance levels, and the scale to which condition-based maintenance is applied.

The current transportation networks face a lot of challenges regarding pollution, noise and costs. The limits of current transportation systems are being pushed and with the increasing number of people travelling regularly, it is clear that new transportation systems must be created to comply with the customers’ needs. Expansion and innovation of transportation infrastructure is needed and future transportation should become more sustainable while also being faster, cheaper, safer, and more reliable.