IMPROVING AIRCRAFT MAINTENANCE WITH INNOVATIVE PROGNOSTICS AND HEALTH MANAGEMENT TECHNIQUES - Case of Study: Brake Wear Degradation

Abstract

Maintenance is going through to major changes in a lot of activity fields where the current maintenance strategy must adjust to the new requirements. The aeronautics industry belongs to one these activity fields which are trying to carry out important changes around its maintenance strategy. It needs to minimize the cost for the maintenance support and to increase its operational reliability and availability (avoiding delays, cancellations, etc) which would lead to a further decrease in costs. However, to support this change, it requires transforming the traditional corrective maintenance practice of "fail and fix" to "prevent and predict". The aim of this article is to show the usefulness and the benefits of innovative techniques such as Bayesian Networks to support an intelligent function "decision support", the basis for the new type of maintenance strategy based on prediction and prognosis. It helps to achieve a maximum optimization of resources and operational availability while minimizing economic costs, and replaces the current maintenance carried out in the aircraft industry up to now.