Data now available about the time aircraft spend on the ground during planned maintenance and refurbishments can play a key role in Predictive Aircraft Maintenance.
Cirium senior director for market development, Andrew Doyle, told the PAM Conference that greater insight into the performance of MROs can be used to better plan scheduled events.
He presented findings that Cirium has generated through its new Ground Events platform that analyses the time aircraft spend undergoing maintenance.
The progress Emirates is making in its fleet-wide refit and the challenges it is facing keeping to original timescales for its A380s and Boeing 777s was highlighted.
Doyle also presented the results of an analysis into a genuine, but unnamed, airline which shoed how its MRO providers are performing against data for other carriers and industry averages.
“The question I really want to pose is, what role can predictive maintenance play in helping to address some of the challenges that we’re now seeing around scheduled maintenance events, Doyle said.
“What we can do, for the first time, with the ground event status is actually track on a day-by-day basis, what is actually happening versus the plan.”
Doyle said this data can help airlines to forward plan for part replacements when their aircraft are due to go in got scheduled C or heavy checks.
“We’re now using this historical tracked data to project forwards. Our data scientists have done a lot of work on the best way to approach this.
“We can track the hours and cycles, but we found pretty much the best way to model this is based on the elapsed time, because the aircraft typically get to the elapsed time limit before they get to accumulate sufficient cycles or flying hours to drive that timing.
“Something we can work on in future is to start to predict how long the ground duration is likely to be based on the typical performance of that MRO provider and the age of the aircraft. A lot of questions in the industry are around whether older aircraft spend longer than expected in scheduled maintenance events.”
Doyle added: “You can also pose the question, can we do something with predictive maintenance capabilities to get a kind of early warning.
“So, when we send this aircraft for a scheduled check, we know there are going to be some issues, maybe with specific components, and they might be difficult to get hold of because of supply chain constraints, or difficult to install because of the skilled labour issues.”
Doyle said the industry is now able to see how predictive maintenance capabilities can help to actually “reduce the level of unexpected findings in these scheduled maintenance events, particularly if parts need replacing and are difficult to get because of the supply chain issues”.
He said: “An example some of the analysis we can do with this global data set is we can look at specific MRO performance. We can look at the service that civic airlines are getting from the group of MROs that they use.
“We can look at that age segmentation, and we can look at any impacts where operators are based in harsh environments. Are they seeing these scheduled maintenance events take longer because of what the aircraft are being exposed to?
Cirium is working with its partner, Matiga in Spain, which has super-computing capability can model the contaminants, aerosols and other particles in the atmosphere.
Doyle said: “We’ve been running an experiment using our Saturn data to actually assess what specific engine series have been exposed to in their day-to-day operation of a three year period. We highlighted some clear links, particularly with dust ingestion and the degradation.
“The next scope is really to look at a bigger pool of assets, a bigger pool of engines, but I think this is really relevant, potentially to predictive maintenance capabilities.”
The post PAM 2024: On-the-ground data’s role in driving predictive aircraft maintenance appeared first on Aviation Business News.