Aviation digitalisation: How big data and predictive maintenance are leading a 'business transformation'

Digital innovations have helped the aviation industry cut costs and increase efficiencies for years now, but what does the future hold on the digitalisation front?

The improved capture and utilisation of big data and the increased sophistication of predictive maintenance were hot topics when the Satair Knowledge Hub spoke with industry experts at the recent MRO Europe conference.

But for many attendees, digitalisation is less about any one specific technology than it is about implementing efficiencies that boost the bottom line. 

“When you talk about digital transformation, at the core, you're solving a business problem,”  Karine Lavoie-Tremblay, Director of Commercial Engines Digital Transformation at Pratt & Whitney, said. “It's coming now to a level of availability and maturity that really [empowers] our employees with the tools that they need to make the right decisions at the right time.”

Sajedah Rustom, the CEO of AJW Technique, agreed that the promise of digitalisation is its ability to allow for faster and wiser decisions.

“When we talk about digitalisation in aviation, I think first and foremost, we’re talking about business transformation,” she said. “Without a strong foundation, there's no technology that's going to work for your environment.”

‘Treasure trove of data’

A common strategy for making better business decisions is harnessing the power of big data. Airlines, original equipment manufacturers, aftermarket players and the maintenance, repair and overhaul (MRO) sector have access to vast amounts of data. This can be anything from flight routes and passenger information to the operational history of nearly every imaginable individual part and component on any given aircraft.

Modern aircraft models are outfitted with thousands of sensors and generate massive amounts of data – thousands of terabytes every single day.

While “big data” has been something of a buzzword in the industry for several years now, Matthew Eli Eli, Satair’s Head of Planning, said that “the treasure trove of data within this industry” means we now know more than ever before.

“We know the aircraft. We know where they're flying. We know the configuration of the aircraft. We know the checks they’re going into and we know the tasks that are going to be performed,” he said.

But Lavoie-Tremblay warned that simply collecting massive amounts of data isn’t enough. You need to know what to do with it.

“Data for data is interesting, but that doesn't necessarily drive value,” she said. “You always need to think about: Where am I going to use this data? What am I using it for? And the more we know, the better suited we will be to respond to our customer's needs.”

Pratt & Whitney, for example, can monitor up to four million engine data points on every single flight. The data collected through its EngineWise system allows P&W’s customers to predict when their engines will need repair and optimise the scheduling of maintenance to minimise ground time.

Predictive maintenance: the new industry standard

The ability to leverage large data sets to better predict and manage maintenance efforts has advanced significantly in recent years. Predictive maintenance is now “the industry standard,” Joost Groenenboom, aviation principal at the consultancy ICF, said.

“The new aircraft, like the 787 and the A350, produce a significant amount of information on their systems and the health of their systems – how valves are opening and closing, how systems are behaving – and based on that information, you can make certain assumptions,” he explained. “You can see that certain systems are not operating in the way that they should be, and hence there might be an issue with it.”

With predictive maintenance, sensor data and maintenance logs can alert airlines to maintenance needs well in advance, helping to plan better and avoid costly groundings. As computational power and data storage capabilities continue to improve, airlines, manufacturers and MROs get access to more and more information that allows them to further optimise their processes.

In short, predictive maintenance allows for what Eli Eli describes as a holistic “bottom up” overview of what’s needed to keep an aircraft in service.

“We're looking at the aircraft going through checks. We're looking at the tasks being performed and we're looking at the material requirements to perform those tasks,” he said.

Whose data is it?

But the collection of all that data leads to an obvious question: Who owns it?

Data is often viewed as a valuable commodity and airlines can be hesitant to share their data with manufacturers, and vice versa.

“There's a discussion currently in the industry about who owns that data and how you use it,” Groenenboom said. “When an airline that has an aircraft that produces this data, it’s obviously their data and they can use it. But if OEMs can gather that data from all the airlines across the world, they're able to very, very accurately predict certain things.”

Similarly, maintenance organisations often have their own data. Rather than collecting data in silos, the various industry sectors should share this information with each other, Groenenboom said.

Rustom said she’d like to see even more data sharing across the industry.

“Big data needs to be open. We need to be able to make decisions on the aggregate. We need to work together in collaboration as opposed to competition and really open up some of the possibilities around digital transformation,” she said. “For me, the foundation of next-generation technologies being successful is really the industry coming together.”

Already, programmes like Airbus’s Skywise work to collect, aggregate and share airline data from work orders, spare parts consumption, component data, fleet configuration, sensor data and flight schedules. Launched in 2017, Skywise hosts data collected from more than 10,000 aircraft operated by over 100 different airlines.

Other popular aviation data platforms include Lufthansa Technik’s Aviatar, Honeywell Forge and Enspan.