LAUSR

Aircraft Maintenance, Repair and Overhaul (MRO) is one of the major components of the Aircraft Life Cycle Cost (LCC). Increasing the efficiency of MRO, as well as reducing MRO cost, is one of the main ways to reduce LCC. In modern aviation technology complexity of Avionics and its maintenance increase. Traditional methods of failure prediction are difficult to apply in complex technical systems which make it necessary to reduce MRO interval. This research proposed the mathematical method of Artificial Neural Networks (ANN) as a possible solution to this problem. The avionics of Unmanned Aerial Vehicle (UAV) is the research object. The reliability and forecasting of failures by traditional and ANN methods have been analyzed, and results comparison are received. The study suggests that the method used is suitable for solving this problem. The obtained results show a high degree of reliability. Further research is proposed to scale to more complex avionics aircraft. The introduction of ANN in the MRO system entails many advantages, including the possibility of increasing the avionics service intervals and failure prediction, taking into account external factors of operation. This will inevitably lead to LCC reduction and increase safety.