A message from Kathy Mackenzie, GEnx Program General Manager at GE Aviation, during the 2017 Paris Air Show.

Big data is everywhere, including aviation.

At GE Aviation, we monitor more than 30,000 commercial engines daily. How much data do we collect? Our engines produce data snapshots at various points in flight, such as take-off, climb and cruise. The snapshots include up to 1,000 different measurement parameters, and each engine can pump out between 50 to 200 megabytes of data per flight depending on the flight time. This gives us a massive amount of data.

The GEnx that powers the Boeing 787 Dreamliner and 747-8 Intercontinental and Freighter has set a new standard for data collection for wide body engines. The engine experienced one of the fastest fleet expansions with more than 1,300 engines flying in just under six years. It took the GE90 eight years to reach 1,000 engines in service.

Kathy Mackenzie, GEnx Program General Manager at GE Aviation

The GEnx engine is also highly utilized by our customers flying passengers, as well as cargo, around the world and accumulating more than 2 million cycles to date.

Finally, the aircraft that the GEnx powers were designed for long flight legs, allowing the engine to amass 12 million flight hours. These unique attributes enabled us to gather a large volume of data very early in the program, and our data analytics are providing significant benefits to our customers.

What makes GE Aviation’s data analytics different? We use our engine design and services experience—how an engine works, how components are designed, how an engine operates in certain environments and our test results. That’s the physics part. We marry the physics with the data analytics that begins with GE’s Predix environment pulling together all the data sets from each engine in operation.

Using the fleet data, algorithms are developed that help us spot trends, identify anomalies and see into the future—to be predictive. We can create a digital twin and predict how an engine will perform in the future. This predictability helps us identify potential problems before they happen.

Customer are feeling the benefits. Data analytics allows us to alert customers to perform simple routine line maintenance efforts to help them avoid inflight issues.

Before analytics, we based things on performing these preventative measures at certain time intervals. Now using the data, we can customize guidance per operator based on their specific engine’s needs.

By linking weather and environmental satellite data of flight routes to engine data, we can see how an engine responds in certain environments. This analysis enables us to recommend operators switch an engine to a less harsh route at a certain point in its lifecycle, giving the engine more time on wing to extend the operator’s usage.

We can also predict shop visits based on an engine’s data to help customers avoid unscheduled engine removals and better plan their maintenance. Reducing inspection and maintenance burden, improving asset utilization and more predictive maintenance – all adds up to a lower cost of ownership for GE engine operators.

As a company, we all are learning how to use big data and data analysis to better support our customers. What’s on the horizon? We are now working on becoming a Digital MRO provider and predicting the engine’s maintenance needs or workscope before it is removed from the aircraft, to enable a faster response and MRO turnaround time.

Experts say about $1 trillion in trapped productivity exists in the aviation industry. GE Aviation and our data analytics efforts are trying to help unleash this productivity for customers. I believe we are well on our way.

Stay up-to-date on all of GE Aviation’s news and announcements throughout the Paris Air Show at geaviation.com/shows!