Predictive maintenance essential to give airports flexibility

Flexibility at the airport is vital because the increased demand for capacity has made turnaround times tighter than ever.

AI-powered predictive maintenance enables airport departments and teams to stay a step ahead by enhancing situational awareness and speeding up decision-making processes. By analysing data from IoT sensors, machine-learning algorithms detect parts that are not performing optimally, enabling timely interventions.

In real-time, an onboard self-diagnosis system, or a diagnosis system monitoring remotely, can alert MRO crews at the airport so they are ready with the necessary tools and parts to carry out maintenance. By adopting advanced tools like Skywise Core [X], airlines enhance their ability to share actionable insights with ground operations, boosting overall efficiency and responsiveness.

They can also recommend predictive maintenance on parts that are not performing optimally – a boost not only for performance but in line with regulatory requirements. AI-powered automated systems, meanwhile, are reducing errors made during handling (baggage, other cargo etc) and increasing efficiency – most notably speed. Finally,

AI-powered systems are optimising both routes and schedules to maximise time efficiency.

Data the missing link for Gen-AI in aviation supply chain

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