Predictive Aviation Analytics


Using Artificial Intelligence to Predict Aircraft Anomalies Helps Save Money & Prevents Delays

Maintenance delays cost the U.S. airline industry over $9 billion per year. World-wide, aviation maintenance costs run about $40 billion each year. Predictive Aviation Analytics (PAA) helps improve passenger safety & on-time performance while substantially reducing maintenance delays. How does it work?

Predictive Aviation offers a breakthrough software program that uses current sensors and Flight Data Recorder (FDR) information to accurately predict probable aircraft component failure. Inflight data is downloaded from the aircraft’s FDR to computers running our software where anomalies are identified and analyzed.

Component failure probabilities are then forwarded to airline maintenance management for action.

Aircraft component failures cause flight diverts, delays, and cancellations. The cost is hundreds of millions of dollars in lost productivity, aircraft and property. New technology can save an airline millions of dollars.

The patent-pending predictive analytics uses computer learning techniques to “weigh” the data for better statistical analysis. When the program recognizes outlying anomalies it sends warning information in time to schedule corrective maintenance. Thus, aircraft are less likely to break down, delay service, or require costly down time while parts are flown in.

Predictive Aviation Analytics may save tens of thousands of dollars each day, as it:

  • Alerts companies of specific planes with a high likelihood of malfunction
  • Permits time to divert an aircraft into preventative maintenance, thus allowing more on-time flights
  • Shortens repair times by reducing diagnostic steps needed to identify the failing part.

Predictive Aviation Analytics also increases safety for passengers & flight crew because it:

  • Reduces in air emergencies through advanced notification
  • Identifies accident precursors to mitigate potential safety hazards
  • Reveals (de-identified) pilot practices that may lead to engine or structural problems

Using Artificial Intelligence for Increased Safety & Reduced Costs with PAA

Predictive Aviation Analytics (PAA) uses compiled flight data from the past to “teach” the computer what sensor information is normal and what sensor information indicates problems. As the program continues to receive data and accurately diagnose high-probability failure, it continues to improve its performance.

This neural network technology learns what values are outliers, and can form connections between different pieces of data to offer a more robust detection of errors and outliers.

The program’s ability to diagnose potential problems far exceeds those of current evaluative software. Predictive Aviation used 1.33% of the data available to the current leading predictive models (FDM/FOQA models) and still outperformed them by up to 70%.

As the program identifies a high-potential danger, it gives avionics mechanics enough data to narrow down the short list of causes for the problems, saving them diagnostic steps.

Please CLICK HERE to contact XFLASH Systems (select Predictive Aviation Analytics from drop-down list) for more info, details or assistance you may require and we’ll be happy to help you, right away! Direct Email: help [at] xflashsystems.com

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