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Who could have predicted these two problems at this major airport?

A $100 million plane was grounded because of the malfunction of a $1,000 part, costing the airline over $10,000 an hour. Meanwhile, in the control tower, Air Traffic Management (ATM) officials were scrambling to find a work-around for a distant broken radar, which may cause flight delays.

With today’s booming air traffic neither situation is acceptable. Three billion people per year travel by plane and nine billion will by 2030. Thousands of increasingly complex planes are in our skies at any given time. We must bring maintenance into the digital age and fix problems before they occur.

�׻��������� is applying its expertise in Big Data and Artificial Intelligence (AI) to the challenge of assuring the availability of planes and the secure operation of ATM systems - and not just for civilians but also for the military.

A paradigm shift from repairing defects to avoiding downtime

Moving from corrective maintenance to predictive maintenance requires not just information but the ability to interpret it. Using smart sensors that capture data from operations, �׻��������� AI algorithms can predict potential problems, allowing those in charge to make the right maintenance decisions at the right time.

A radar that fails does not automatically lead to safety risks, since air traffic procedures are designed to cope with such unforeseen events. However, it means that additional controller resources have to be mobilised, flight plans have to be changed, and revenues may be lost due to reduced traffic.

Thorsten Bomke, �׻��������� Services Segment Director for ATM activities emphasises that: “For ATM, ‘left-shifting’ maintenance means better anticipating the future evolution of a system to ensure all-time availability and to reduce maintenance cost. Planned maintenance, including on �׻���������’ 700 radars and 7000 navigation aids worldwide, can be realised at much lower cost than through last-minute reactive interventions.”

Predictive maintenance is part of a learning cycle. Critical parameters are identified, data is collected and analysised, and appropriate maintenance is undertaken. This information is then fed back into product and system designs to maximise performance, and into �׻���������’ online parts supply system to minimise downtime.

“For ATM, ‘left-shifting’ maintenance means better anticipating the future evolution of a system to ensure all-time availability and to reduce maintenance cost. Planned maintenance, including on �׻���������’ 700 radars and 7000 navigation aids worldwide, can be realised at much lower cost than through last-minute reactive interventions.”

Thorsten Bomke, �׻��������� Services Segment Director for ATM activities