Abstract
Abstract: Anticipating aircraft breakdowns is one of Industry 4.0's primary goals. It's critical to be able to prevent failures since downtime costs money and results in a loss of productivity. That's why it's critical for aircraft maintenance to figure out how many cycles or RULs are left till the breakdown occurs. The RUL estimates should be based on earlier observations wherever feasible under the same conditions. The research of RUL estimation is primarily centered on the creation of systems that monitor the current condition of equipment. While this topic is extensively researched, there is no single universal approach. This concept, which employs recurrent neural networks (RNN) for the predictive maintenance of the planned system, is motivated by the lack of a generic technique
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