New generation aircrafts like Boeing 787 Dreamliner or Airbus A350 are getting smarter. They are even more connected than the passengers they carry. According to Airbus, its A380 superjumbo — which first flew a decade ago — collects information on more than 200,000 aspects of every flight. With one terabyte of data generated on every flight, aircraft manufacturers are considering how to leverage the information they gather across their global fleets.
The aviation industries are excited about this wealth of data. Aircraft manufacturers are now discussing predictive maintenance or fixing the aircraft before it breaks down. If the crucial parts are fitted with sensors, they will be able to transmit information to engineers on the ground, who will be ready and waiting with parts when it lands. Therefore, the aircrafts will not be grounded for maintenance.
But there are limits to this blue skies scenario, not least the ability to filter out the bits that matter from the thousands of terabytes generated every day.
“It is complicated,” Randy Tinseth, Boeing’s head of marketing. “An engine tends to have one manufacturer and a data-rich environment. With an aeroplane, you have hundreds or thousands of suppliers. There are 21,600 aircraft flying today and each has a wide variety of capability in terms of information. It is an apples and oranges world.”
Another industry executive suggests there is a lot of hype around the potential for mining this mountain of data in radically new ways.
“We have always had this data,” he says. “But it is like teenage sex. Everyone is talking about it and saying they’re doing it, but we know it isn’t happening.” One of the biggest obstacles — in the short term at least — is the lack of sufficient communications infrastructure to harvest and transmit the data, according to Mr Stein of Rolls-Royce. “Current technology restricts us to a few tens of kilobytes of information in flight.
Eventually however these obstacles will have to be overcome. As each generation of aircraft and engine arrives, big efficiency gains are becoming harder to achieve. Further progress may depend on knowing where the richest seams of real-time data lie. “Over time the information will be better understood,” says Mr Tinseth. “But it will take time.”
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