SkyMaintain: ai-backed predictive aircraft maintenance system

Moses Olushola Onilede

doi:10.14419/f2v3n369

Authors

Moses Olushola Onilede
Institute of Aeronautical Engineers

Received date: October 20, 2024

Accepted date: October 21, 2024

Published date: December 26, 2024

DOI:

https://doi.org/10.14419/f2v3n369

Keywords:

AI-Powered Maintenance; Aircraft Systems; Predictive Analytics; Aviation Safety; Maintenance Technology

Abstract

SkyMaintain is an AI-powered aircraft maintenance system designed to predict potential faults (snags) in aircraft systems before they occur while providing technicians with real-time, regulation-compliant maintenance guidance. The system integrates predictive analytics, historical maintenance data, and regulatory compliance protocols to offer proactive maintenance solutions and reduce aircraft downtime. The system enhances decision-making during aircraft maintenance procedures by incorporating AI algorithms capable of learning from real-time sensor inputs, operational metrics, and environmental factors. This paper presents the design, implementation plan, and testing framework for SkyMaintain, highlighting its innovative potential in revolutionizing aircraft maintenance practices. The system’s architecture, which includes a user-friendly interface, cloud-based maintenance logs, and an automated compliance checker, ensures ease of use and adherence to aviation safety regulations. The study concludes by discussing the system’s impact on maintenance efficiency, future scalability, and its potential to enhance safety and reliability in aviation operations.

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