Journal of Airline Operations and Aviation Management

The primary difficulty in aviation is evaluating the life of aircraft engines (AFs) in order to ensure that people on board and precious goods are transported safely from one nation to another. other nations at the port of arrival To foresee and anticipate all of these possibilities, we suggest combining AI and Deep Learning with a short-term memory (LSTM) neural network to forecast when the aircraft's engine will need to be fixed or replaced. The collection is needed of past aircraft history data with 21 sensor readings for each aircraft to make these predictions. Aircraft have three alternative settings = s1,s2,s3 so that data may be manipulated and the relationship / trend in the data can be discovered, allowing our system to forecast the remaining usable life (RUL) of an aircraft engine.