Web-based tool for predicting the Remaining Useful Lifetime of Aircraft Components

Applications of Machine Learning in Aircraft Maintenance

“…SBMs are a generalization of minimal distance (MD) approaches, which are used in a variety of machine learning and pattern recognition algorithms [22,25]. A nearest neighbour approach is used in similarity, a machine learning technique, to compare two or more objects using algorithmic distance functions [30,45].…”

“…Extrapolation is a method for estimating the value of a variable beyond the initial observation range based on its relationship with another variable [22]. Extrapolation is similar to interpolation in that it provides estimates between known observations, but it is riskier and more likely to produce meaningless results.…”

“…Nuhu et al [21] investigated the applicability and effectiveness of ML prediction models for fault diagnosis in smart manufacturing. In predicting the Remaining Useful Lifetime (RUL) of aircraft parts, Azevedo et al [22] developed a web-based application. This application models a Prognostics and Health Management (PHM) system with an aim of forecasting the RUL of specific aircraft parts by implementing various machine learning algorithms such as these three proposed methods: extrapolation-based method, similarity-based method and neural networkbased method.…”

“…Different neural network types such as artificial neural network (ANN) and convolutional neural network (CNN) operate according to various principles and establish their own rules. A neural network (NN) is artificial neuronal circuit [22]. The connection of neurons is modelled by ANN as weights between nodes.…”

“…The replacement of aircraft components is one of the most significant tasks performed by the aviation maintenance staff [22]. Instead of doing scheduled maintenance at predetermined intervals, replacement may be necessary based on the state of the aircraft component to maximize the lifetime of the aircraft equipment [25,26].…”