Failing And Not Falling (F&!F): Data-Enabled Classification Learning of Aircraft Accidents and Incidents
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(2020) 4:9
ORIGINAL ARTICLE
Failing And Not Falling (F&!F): Data-Enabled Classification Learning of Aircraft Accidents and Incidents Jarrod Carson1 · Kane Hollingsworth1 · Rituparna Datta1 · Aviv Segev1 Received: 11 February 2020 / Revised: 5 October 2020 / Accepted: 4 November 2020 © Springer Nature Switzerland AG 2020
Abstract Journey by aircraft is the only option for long-distance transportation and also one of the frequently used modes of transportation of passengers. As a result, safety of passengers and efficiency of the aircraft depend on maintaining efficient running conditions. Although many safety standards are followed in the design of the aircraft, and thus there are fewer accidents, it is necessary to perform a thorough analysis to avoid risks that may occur during flight time. In the present work, we propose a maintenance strategy, Failing And Not Falling (F&!F), based on the Federal Aviation Administration (FAA) data in the USA. We work with the dataset of Boeing 737. The data consists of 72 features with 137,236 records which describe an aircraft accident or incident. These features are used to predict whether an incident will be identified during aircraft maintenance or during aircraft operation and what specific type of incident will occur. The prediction method is based on the integration of a decision tree and a unique neural network at each node of the decision tree. The results obtained using different architectures show how deep the neural networks should be, how to identify the relevant features, and the success of combining decision trees and neural networks. Moreover, the neural networks and the decision tree approach also successfully identified the important features of maintenance. This method can be used for the maintenance of any data in multiple domains. Keywords Machine learning · Decision trees · Neural networks · Maintenance · Aircraft
Introduction An aircraft is a very complicated dynamic system with interactions between several components. As a result, with
This article belongs to the Topical Collection Data-Enabled Discovery for Industrial Cyber-Physical Systems Guest Editor: Raju Gottumukkala Aviv Segev
[email protected] Jarrod Carson [email protected] Kane Hollingsworth [email protected] Rituparna Datta [email protected] 1
Department of Computer Science, University of South Alabama, Mobile, AL, USA
the increase in the life of an aircraft, all the parts are exposed to different environmental, abnormal, and stress conditions which not only deteriorate the performance of the aircraft but also have an adverse effect on the structural components. Hence, maintenance of each sub-component as well as the overall system is necessary. The goal of all airline companies is to have a better overhaul, repair, and maintenance strategy to ensure the safety of passengers, improved quality of service, and minimization of running cost within minimum budget and schedule. A failure in one of the components of the aircraft may damage the whole sys
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