Impacts of a Prognostics and Health Management System on Aircraft Fleet Operating Cost during Conceptual Design Phase by using Parametric Estimation
The scope of the study is to analyse the operating cost of an aircraft fleet during conceptual design phase, when installing a Prognostics and Health Management (PHM) system. Part of the work is devoted to the process and related methodologies aimed at estimating the cost in in a very preliminary phase of the life cycle, as an approach for the necessary trade off. The cost estimation is carried out by using commercial and proprietary software in order to show common views of different approaches. These tools perform parametric cost estimation exploiting a relative small quantity of cost drivers, which are available since the initial phase of the project. Maintenance parameters are identified through statistical methods, “knowledge based” approaches. To quantify the effect of the introduction of a PHM on a complex system, such as a commercial transport aircraft, is quite uncertain in early design phase and it is worth to be investigated. PHM technology can be adopted for each aircraft main component [1, 2, 3] and, as the other aircraft on-board systems, introduces additional maintenance cost (even the PHM system sensors and computer may have a fault) and sometime it notices false positive detections determining unnecessary maintenance actions. On the other hand, PHM is able to: extend the aircraft components service life, reduce the number of necessary spare parts, lessen the repair time (maintainers are aware of the failure location) and optimize the maintenance activities also increasing the aircraft availability. For a commercial transport aircraft, more availability means more flights and revenue. To properly estimate the effect of the maintenance optimization it is necessary to examine a complete aircraft fleet. This is suitable considering that maintenance team, maintenance management and aircraft operation are subjects designed for a fleet of aircraft instead of the single one. To better calculate aircraft fleet parameters, it was necessary to develop an environment in which the fleet operation is simulated. Moreover, to obtain actual operating parameters the model has to include Monte- Carlo methodology [4, 5] in which some important variable, such as failures, repair time etc., should be simulated using a stochastic approach. From the cost estimation point of view, to evaluate the effect of the PHM system it is essential to include each items of the Life Cycle Cost (LCC). The tools used [6, 7] has to evaluate the cost before the detailed design phase. Spares and maintenance labour cost are directly affected by PHM system, however considering maintenance optimization issues, also fuel and spares management have to be taken into account. Other important cost items are related to the number of flight (i.e. aircraft availability) and the reduction of flight delay and cancellation due to unscheduled maintenance action. A final comparison based on LCC is made between aircraft fleets in a configuration with and without the PHM system, to show the results and the main differences.