INSIGHTFUL MRO

Predictive maintenance is a clear digital priority for MROs. This transformative approach enhances efficiency, reduces costs, and minimises downtime, addressing evolving challenges in fleet management, writes ATUL CHANDRA

- ATUL CHANDRA

The aircraft Maintenance, Repair And Overhaul (MRO) industry is moving towards the greater use of Artificial Intelligence (AI) based predictive maintenance to increase efficiencies.

Airlines invest extensive resources in aircraft MRO, which is key to keeping their fleets safely in the air. However, older MRO methods and practises feature paper heavy processes, which track the various routine checks that have been performed at predetermined intervals. Historically, it has been difficult to analyse the data in a timely fashion to undertake the maintenance, repair or replacement of parts before their performance starts to suffer or they break down. The industry also continues to face evolving challenges related to supply chain complexity, talent shortages, and rising competitive pressures. Airbus has estimated that the market for aircraft aftermarket services will reach $290 billion globally in 2043, up from $150 billion in 2024. It also estimates that operational inefficiencies would cost the airline industry an estimated $70 billion in C2030, but digital services could address up to one-third of that figure.

However, modern commercial aircraft gather vast amounts of data from their sensors and computers, which, coupled with the server capacities, transmission speeds and self-learning algorithms already available today, make it possible to automatically aggregate and analyse huge quantities of data. A typical A320, for example, has over 180 monitored airframe and systems items, including complex systems such as those related to hydro-mechanical, electrical and fuel system parts. As an example, one year of 787 sensor measurements from one airplane results in 1TB of data.