Until recently, the maintenance department at Emirates, the Dubai-based carrier, was operating by the book. Literally. Ground crews used detailed charts and calendar-based schedules to estimate when the engines powering its massive fleet of Boeing 777 jets needed service.
Airline managers scheduled maintenance every 400 to 600 flight hours — even if nothing was wrong — to perform routine preventative work on their GE90-115B engines, incidentally the most powerful jet engines in the world.
The process yielded a fleet of healthy jets, but at times involved grounding planes that were perfectly fine to fly. On the flip side, the airline also had to perform unscheduled and expensive emergency maintenance when problems popped up earlier than expected. With its extensive network covering six continents, Emirates has to regularly cope with weather and other conditions that are less than ideal for airplanes.
These unplanned pit stops could disrupt the airline’s schedules, not to mention lead to extra costs and personnel planning, says Ahmed Safa, Emirates’ divisional senior vice president of engineering.
But things are changing. Emirates recently started using GE’s Analytics Based Maintenance software, or ABM, to minimize surprises. ABM uses data gathered from many sensors fitted on each plane to monitor engine health and predict potential problems before they become problems.
So far, GE has installed thousands of sensors on 160 Emirates 777s. The sensors gather data on everything from operational parameters like temperature and vibrations to flight time and speed to weather conditions. That real-time monitoring of each engine allows engineers to spot problems early, and send engines for servicing before they fail and cause disruptions.
Top: GE has installed thousands of sensors on 160 Emirates Boeing 777s. The sensors gather data on everything from operational parameters like temperature and vibrations to flight time and speed to weather conditions. Image credit: Getty Images. Above: Emirates jet engine test facility in Dubai. Images credit: GE Aviation.
Engineers at GE’s Middle East Advanced Aviation Technology Center in Dubai, which opened in 2015, have been using GE machine learning software to analyze 10 gigabytes of data per second. The insights provided by the algorithms allow the team to design digital models that predict the optimal time for preventative maintenance for each engine. That keeps engines running at peak performance for longer periods, so they have shorter routine downtimes and significantly fewer breakdowns. That boosts efficiency and decreases costs. In fact, Emirates has reduced unscheduled maintenance by 50 percent and increased engine “time on wing” 20 percent with ABM. That’s led to more efficient and effective use of staff resources for maintenance, since people aren’t being regularly reassigned to emergency repairs.
“ABM allows us to address those engines that require the highest attention by proactively removing them from operation, and saves us money because now maintenance is only performed when warranted,” Safa says. “This has made our engine maintenance program more stable and predictable.”
One of the key elements of ABM is the ability to spot problems as they are occurring. That means engineers can “see” the engine’s current health, estimate its future problems and share the information easily and accurately between shifts and even between airports.
But ABM helps beyond smart maintenance. Crews can use it to operate the engines in the most advantageous way — optimizing fuel burn and reducing jet fuel costs. Engineers are also integrating the real-time data collected from engines with their maintenance histories. That will allow the teams to develop a framework for continuous improvement, and gain ever more insight into root causes of performance and mechanical issues.
All this means that Emirates is no longer tied to a calendar-based maintenance program. Rather, it can create customized maintenance plans for each individual engine. “ABM gives us an engine-specific view of the fleet that allows for a more targeted approach,” Safa says.
He admits there was a learning curve while the entire organization shifted its mindset to an “engine-by-engine” assessment and management approach. “That was critical in implementing ABM, because any change in fleet management practices had to be extrapolated across more than 160 flying aircraft and around the globe throughout the entire maintenance department,” Safa says.
But in the long run, all the growing pains were worth it. “ABM is a groundbreaking tool that allowed us to achieve significant stability and cost savings,” Safa says. “We are already working on options to expand the scope of ABM that hopefully will lead to even more operational and efficiency gains.”