Big data breeds big talk in some circles, but two European airline engineering companies unveiled tools to help turn the volumes of information flowing from aircraft and engines into actionable, predictive maintenance, during Aviation Week’s MRO Europe Conference & Exhibition.
Lufthansa Technik’s (LHT) Condition Analytics tool combines condition monitoring with predictive maintenance into a single, independent platform that can be used for mixed fleets. Use of the tool, which is not predicated on being part of an LHT support contract, is designed to maximize component reliability, availability and safety.
“We’re joining teams of engineers, data scientists and data architects to correlate causality to save operators money,” says Jan Stoevesand, head of analytics and data intelligence within the information management segment at LHT. This co-located team approach replaces one dominated by troubleshooting and condition monitoring.
One thing that makes LHT’s “highly intelligent platform” unique is that others feature vibrant analytics and algorithms, “but without airline operations and engineering know-how, you won’t find the use cases,” says Stoevesand.
As an example, Condition Analytics saved 1% in fuel burn by identifying that an aircraft’s flight controls were not flush and needed to be rerigged, says Helge Sachs, LHT vice president for corporate innovation and production development.
Through Condition Analytics, LHT also reduced technical delays by 25% by identifying contradictory results from height sensors that caused an autopilot landing system to fail. The data analysis identified which sensors needed to be replaced before they failed, to solve the problem and increase aircraft reliability.
“It’s not about the technology. The big question is what added value you are bringing to customers like this Condition Analytics tool provides,” says Sachs.
Stoevesand thinks “big data” and “predictive maintenance” often can be buzzwords. “We’re changing this by having condition-monitoring integrated with predictive to show the state of an aircraft and its future state,” he says.
Like LHT, Air France Industries KLM Engineering & Maintenance (AFI KLM E&M) continues its shift toward using predictive-maintenance models and announced its Prognos tool, a range of software solutions based on exploiting data from aircraft systems to improve maintenance models and processes.
Developed as part of its MRO Lab program, whose staff has undertaken numerous innovation-driven projects, Prognos is designed to target customer cost savings by harnessing big data to predict failures before they occur.
The package represents a “significant new offering,” says AFI KLM E&M’s senior vice president-commercial, Fabrice Defrance, who notes that along with its technical capabilities, Prognos creates a new business opportunity. “Maintenance is no longer preventive. It’s now more than that; it has become predictive,” he says about why the new offering was developed. “Prognos will be part of our basic services, within the support we are providing, benefiting both aircraft operators and ourselves.”
Defrance anticipates Prognos will be beneficial to both customers and AFI KLM E&M itself. “When we predict that we have to remove a component earlier than what we would have done with previous systems, it’s a positive for the operator as issues like an operational incident, a late departure or an AOG [aircraft-on-ground] situation can be avoided,” he says.
Prognos’s first customers are Air France and KLM, the two carriers that formed the MRO’s airline parent group after the French and Dutch flag carriers merged in 2004. Both airlines are testing the first parts of the Prognos offering—Prognos Engine Health Monitoring (EHM)—along with the Prognos A380 application, which is used to monitor data from their fleets of the Airbus mega-transport.
The EHM platform provides statistical analyses of engine data to enable monitoring and predict failures using an early warning system across the fleets of both airlines. AFI KLM E&M says it also is developing a similar program to the A380 module for tracking aircraft systems and components for the Boeing 787.
Drawing on its airline-affiliated MRO status—meaning it is exposed to high volumes of data sets—works to Prognos’s advantage, according AFI KLM E&M’s director of innovation, James Kornberg. “Having full access to aircraft-generated data, and robust technical expertise of aircraft systems and sub-systems due to its MRO and airline profile, endows AFI KLM E&M with genuine legitimacy to develop this type of solutions,” he says in a statement.