Finnair had a problem that costs it about €100 ($130) per minute and it needed a solution.

The culprit was the dual engine bleed air system on its Airbus A330s. The airline suffered two incidents because the system failed—each malfunction resulted in loss of aircraft pressurization and resultant emergency descents.

Finnair flies its eight A330s and A340s about 19 hr. per day “so even a one-hour delay can cause a mess for a week,” says Manu Skytta, assistant VP of component services for Finnair Technical Services. Over the past 12 months, the airline has logged about 20 hr. of delays with these aircraft due to the bleed system, so a solution definitely was needed to ensure that these airplanes would be able to produce the high-dispatch reliability rates they are noted for.

Skytta wondered if the airline could use the parameters from the bleed-monitoring computer to forecast bleed system faults and component removals. It had the data but needed to figure out how to detect anomalies in aircraft subsystems, so it could “predict as many critical events as early as possible,” without generating false alarms, ideally with a signal-by-signal approach, he says.

Enter Frankfurt Consulting Engineers (FCE), a company that develops mathematical algorithms to improve industrial production. One of its tools is Hazard Predictor—a data-driven condition monitoring system that uses algorithms to detect deteriorations.

Seeing its problem growing worse, Finnair decided to put its faith in math because something needed to be done. “The longer a critical event lasts, the more critical it is,” says Skytta.

Finnair started sending raw aircraft signal data via a file transfer protocol server and asked FCE to figure out what was wrong with the aircraft’s system, even though the company has no aircraft background. Just to emphasize this point: FCE’s employees are highly intelligent, but they are not aircraft engineers or maintainers.

FCE received the flight data weekly, input it into its condition-based monitoring tool, analyzed the data clusters and sent Finnair weekly reports detailing which aircraft parameters included anomalies that could become critical.

First Warnings

Between May 1 and Sept. 13, Finnair removed 26 components related to the bleed system in its A330 fleet—11 of them related to the bleed system computer. Of those 11, the problems were associated with high-pressure bleed valve (three), bleed valve (two), check valve (two), bleed monitoring computer (one), trim air valve (one), trim air pressure valve (one) and air supply valve (one).

Not to pick on Airbus, but the Hazard Predictor forecast the first warnings of each of these problems before the manufacturer’s Airman aircraft health monitoring system did, and sometimes Airman did not provide a warning at all.

Nathalie Willig, a project manager for Airbus’s customer services operation, says Airbus is working on its predictive techniques with Airman.

Skytta says Finnair focused only on these eight aircraft’s bleed monitoring computers for six months as a proof of concept to see if it resulted in fewer component removals and maintenance-related delays. While he believes the Hazard Predictor “shows clear potential for specific systems and components,” Skytta acknowledges that a bigger fleet over a longer time period should be tracked.

Finnair and FCE are looking for other airlines that might like to be part of the next stage of this project. Airlines should contact Daniel Jaroszewski, project manager for aviation monitoring systems at FCE Frankfurt.

Skytta says Finnair might want to use this type of monitoring for its Airbus A321s and A350s on order.

With new aircraft and engines offering so many health-monitoring parameters, it is good that airlines are devising new ways to use those data to increase reliability.