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The short answer is this: IoT technology is changing the aviation industry in multiple ways. Indeed, IoT sensors support continuous monitoring of aircraft systems in flight to create more effective predictive and preventive maintenance, leading to fewer failures and more reliable (and more efficient) operation.
Today's aircraft are abundant with internet of things (IoT) sensors. The latest generation of aircraft has essentially become a flying network producing vast streams of real-time performance data. In fact, the 787 aircraft transmits 28 times more data in flight than a 777.
Sensors monitor temperature, pressure, vibration and other physical performance and environmental measurements, and then stream the data to service and support facilities on the ground. The data is fed into analytical programs that watch for any deviation from the norm, any unexpected change and evidence of wear or impending failure.
All engine components, hydraulics and vital flight systems are repaired based on onboard sensor readings (cockpit indicators and alarms), and they are routinely maintained on a scheduled basis (based on flight hours, number of landings, etc.) The routine maintenance and replacement cycle depends on engineering studies and performance history to predict the normal useful life of each component. The biggest risk in this approach is that normal does not accurately predict the performance or history of any one particular aircraft.
If the normal useful life of a part is, say, 10,000 flight hours, the maintenance schedule might call for replacement at 7,000 hours for safety. It's entirely possible, however, for one of these parts to fail at 5,000 hours -- or 4,000 hours. Another might have an actual useful life of 15,000 hours and be replaced before its time.
Using sensors to monitor conditions and performance in actual operation can often detect signs of early impending failure. Scheduled maintenance actions for otherwise fully functional components can also be extended, although not indefinitely, for more efficient maintenance. Routine replacement for our fictitious example might be extended to 12,000 hours, for example, unless the sensors detect signs of degradation.
More performance and maintenance data via IoT technology can also help the repair facilities operate more efficiently by taking the aircraft out of service for repairs of failing components less often, and by better scheduling preventive actions. More data and better planning can also lead to more efficient positioning and provisioning of parts and equipment.
Predictive maintenance, based on the increased use of IoT sensors, is a great example of the ways in which IoT technology and big data are being used to boost aircraft safety in newer machines. Air passengers and air cargo shippers can feel more confident that flight operations are efficient and safe because of predictive maintenance based on IoT.
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