Implementing IVHM on Legacy Aircraft: Progress Towards Identifying an Optimal Combination of Technologies

The aim of Integrated Vehicle Health Management (IVHM) is to improve the management of maintenance operations through the implementation of health monitoring tools on key components either by diagnosing deterioration or by estimating Remaining Useful Life (RUL) so as to effect timely, and cost effective, maintenance. Regarding the use of IVHM technology in legacy aircraft, one has to keep in mind that hardware modifications to improve the reliability of components is not normally considered a viable alternative to diagnostic and prognostic tools due to high certification costs. At the same time, the data and expertise gathered over years of operating the aircraft help to estimate much more accurately how different health monitoring tools could impact maintenance activities. Consequently, selecting the optimal combination of health monitoring tools for legacy aircraft is significantly easier than for a new design. While computer simulations of the maintenance process are essential to determine how different IVHM tools generate value for the stakeholders, it is not practicable to simulate all possible combinations in order to select which tools are to be installed. This paper describes a process to reduce their number of toolsets to be simulated starting with the identification of those components that present a higher potential to reduce maintenance costs and times in case their faults could be detected and/or predicted. This is followed by the definition of the minimum required accuracy of diagnostic and prognostic tools for each component. This enables designers to determine which tools—available or still being developed—can be implemented to achieve the expected improvement in maintenance operations. Different combinations of IVHM tools are then subjected to a preliminary risk and cost-benefit analysis. A significantly reduced number of combinations are then simulated to select the optimal blend of technologies.