INTEGRATED LOGISTICAL SUPPORT OF AERONAUTICAL EQUIPMENT BASED ON PROBABILITY-GUARANTEEING ESTIMATION OF THE RISKS, ASSOCIATED WITH THE AIRCRAFT TECHNICAL CONDITION

Abstract

In this article, we analyze the modern concepts in the field of the aeronautical equipment integrated logistical support (ILS). The key element of the traditional logistical support system under consideration is the data on detected failures and malfunctions, recorded in the air flight and maintenance log (AFML), chart-orders, non-routine write-ups and accumulated within the structure of the logistic support analysis database. We propose a method for expanding the ILS capabilities by means of including of an additional element, called the flight information database, in the logistics center structure, along with the traditional database for analyzing the logistical support. This database is constantly growing during the aircraft operation. It also contains the values of the parameters recorded by the standard onboard flight data recorder, which reflect the state of the onboard systems. The inclusion of a flight information database into the structure of the logistical support center makes it possible to implement the probability-guaranteeing estimation method in respect of the risks, associated with the aircraft technical condition, for benefit of the integrated logistical support. The proposed method uses an inverse probabilistic criterion (quantile) as an integral characteristic of the aircraft systems technical condition. This is fully consistent with modern approaches to organizing condition-based maintenance. Among these approaches, the data-driven methodology (DDM) has the greatest potential and practical efficiency. The applicative value of the described method is in the fact that its implementation needs neither a priori information about the principles of the maintained equipment operation, nor information about the functioning principles of the on-board controller network, which is used to control the equipment physical parameters. In this article, we also present the accuracy estimates of forecasting the residual life of an aircraft gas turbine engine, using the proposed method. These estimates are based on the actual flight data presented in the National Aeronautics and Space Administration (NASA) repository.