Reducing Flight Delays with AI and Analytics

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Flight delays

There are few occurrences that aggravate airline passengers as much as flight delays. And many flight delays begin with weather issues, personnel problems, and/or maintenance issues on aircraft.

And while we can now get email or text notifications, it’s still a problem for passengers who can be left in the dark as to why their flight is delayed, when they may be leaving, and what other travel options they may have.

The way today’s airlines operate – having one aircraft arrive at a location just in time to refuel, clean the cabin, and depart again can create challenges when problems arise. If an aircraft is delayed because of weather at one airport or mechanical problems in the air that need attention when they land, this “just in time” approach to flight scheduling can result in a snowball effect that impacts multiple other flights in multiple other destinations and airports.

But there are ways that these flight delays can potentially be alleviated. And it doesn’t require any drastic changes to how airlines operate or conduct flight scheduling and planning. All it requires is better use and analysis of data.

IoT + U = smarter aircraft maintenance

The number of Internet of Things (IoT) devices in the aircraft and aviation industry continues to grow at unprecedented rates. Today, for example, there are network-enabled smart sensors, which are incorporated into the systems that are prone to maintenance issues on certain fleets and that are rich in sensor data.

By leveraging the data these sensors generate, more proactive maintenance can be implemented, and future flight delays can be reduced.

Leveraging the data available from these systems, airlines can make more insightful maintenance decisions and become more proactive in their aircraft maintenance.

If several systems across multiple aircraft fail after a specific amount of use or after a certain number of flights, an airline can proactively make the decision to replace parts or service those systems prior to meeting those benchmarks. That maintenance can be scheduled during off hours and when the aircraft is not in use, eliminating the need to pull it out of service at a later date when the system or part ultimately fails.

Granted, there are some systems within an aircraft that have yet to embrace IoT and network-enabled smart sensors. However, we are seeing significant IoT growth in areas such as the interior of the aircraft, from sensors in coffee makers to more connected first-class seats.

Over time, we will see more sensors onboard aircraft, and there will be data about virtually every part of the plane. By leveraging the data these sensors generate, more proactive maintenance can be implemented, and future flight delays can be reduced.

Getting foresight into flight delays

But what about other issues, such as weather, that can cause flight delays? Companies like Collins Aerospace have been working for years to develop predictive solutions that can be used to improve airline operations by taking into account environmental conditions. These solutions use artificial intelligence (AI) and machine learning (ML) to predict the time an aircraft will arrive at the gate (IN/EIBT) and arrive on the runway (ON/ELDT).

The results of this work are solutions such as FlightAware Foresight, which gives airlines access to continually updated ETA information that is 30 percent to 50 percent more accurate. These predictions take several different factors into account, including weather, aircraft positions, arrival gates, operating carriers, aircraft type, and more.

When you consider that an aircraft might have to then be turned around and prepared for another flight to a different destination, it’s easy to see how these small inefficiencies can snowball into larger delays.

This can help airlines make better decisions around the utilization of aircraft, personnel, and space – such as gates. For example, airlines can make decisions to swap aircraft or crews used on particular flights in the event of early arrivals or delays. They can ensure gate space is being allocated properly based on predicted arrival times and not simply relying on planned schedules. The same data could also be used by ground handlers to ensure crews are prepared for early or late aircraft arrival so that flights don’t sit on the tarmac waiting for a crew to arrive to meet the aircraft.

While waiting 15 minutes for a crew to come and meet an aircraft that has landed and is sitting on the tarmac might not seem like a long time, each little, inefficient delay can add up. When you consider that an aircraft might have to then be turned around and prepared for another flight to a different destination, it’s easy to see how these small inefficiencies can snowball into larger delays.

Data, data everywhere

As aircraft, airports, and airlines become increasingly connected, data creation will accelerate. Data will continue to be created, captured, copied, and consumed more quickly. Data will be everywhere – and that can become daunting. With data everywhere and being generated by everything, how can airlines leverage it for insights?

Data comes in all forms and sizes and is dispersed in many different on-premises or cloud environments. To make the most of its data, airlines need to identify and execute a data lake or data warehouse strategy. Most data is generated in a raw format – a JavaScript Object Notation (JSON) from an IoT device or a table from an application database. This data needs to be cleaned, tagged, and aggregated with business logic before it can be leveraged and analyzed to derive data-driven insights. 

The data is there – and more of it is on its way.

Identifying and implementing a data strategy can be difficult, and a high bar of entry before they can begin to truly leverage their data for operational insights. This is why it’s essential to work with technology partners that understand the commercial aviation industry, have a deep catalog of historical data to reference, and have relationships with the leading AI and cloud solution providers that allow them to market-leading solutions to bear for their customers.

Operational challenges like flight delays cut into an airline’s profitability and hurt its bottom line. They also anger passengers and damage brand loyalty. The data is there – and more of it is on its way. By partnering with trusted industry experts, airlines can put the solutions and strategies in place that will enable them to leverage that data to improve operations, eliminate operational problems – like flight delays – and improve their profitability while making their passenger experience better.

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