But predictive possibilities differ from component to component. For example, for engines and APUs, systems can suggest maintenance actions, but only trend data is offered and flagged green, yellow or red for many other components. Someone at the airline or elsewhere must then decide what to do.
Law says one improvement would be giving ground staff the ability to request more data from onboard systems automatically, without talking to pilots. “But there are certification issues to sending messages in flight,” she notes.
Airframe OEMs have joined engine makers in monitoring aircraft performance. Airbus's AIRcraft Maintenance Analysis (Airman), used by 106 customers, constantly monitors health and transmits faults or warning messages to ground control. The tool offers rapid access to maintenance documents and troubleshooting steps prioritized by likelihood of success.
Airbus's new Real-Time Health Monitoring (AiRTHM) goes further as systems on new aircraft yield more parameters, and the Aircraft Communication Addressing and Reporting System (Acars) enables Airbus to collect and analyze data from remote locations in real time.
It is developing AiRTHM in its Airtac (Airbus Technical Aircraft-on-ground Center) maintenance control center to give real-time troubleshooting assistance, guide spare provisioning and monitor system health to anticipate failures. It is available to ease the A380's entry into service, and it will be extended to A380 Flight-Hour-Services customers as well as supporting the A350.
Boeing's Airplane Health Management (AHM) is used on 2,000 aircraft for 53 customers. Dave Kinney, associate technical fellow in commercial aviation, describes AHM as “part of one pathway toward predictive maintenance. We see three primary elements: experience such as knowledge of aircraft design; tools like AHM and other analytical tools; and data, including operational and maintenance data.”
Looking at multiple data sources yields richer possibilities for prediction, and flight-data recorders capture and download huge data files in flight or on landing. Kinney says both physics-based and statistical methods are necessary for the best predictions.
One emerging tool, associative memory, maps connections between text and data from many different systems, much like looking for connections in the human brain. “Advanced analytics applied to more disparate data sources—that's how we are going to crack this,” Kinney says.
But a culture change is also necessary. “Mechanics are not used to removing a component because experts predict it will fail next month,” he notes. “This culture change is still in its infancy, even with high-value assets like engines.”