march2021 - 23

not been generated for almost a year now as the aircraft didn't
operate, " said de Bree.
" It [predictive maintenance] is somewhat static from the perspective of there are fewer aircraft flying and there are fewer hours
flying and so you don't have as many issues or disruptions as you
used to, so it's hard to advance. When you talk about big data, if
you've got a lot of data flowing, you'll be able to advance what you're
doing. When there's not a lot of data flowing it's very difficult to
advance what you're doing, " Peterson added.
Though, the industry groundings have opened doors for possibilities as well, noted Elliott. " The commercial aviation industry is going
through major disruptions due to the pandemic and airlines, OEMs
and MROs alike are changing their business models to capitalize on
new technologies - in particular Digital Twins, but also Artificial
Intelligence, IoT and more. These innovations are all gathering key
data and are paving the way for predictive maintenance to make
even greater strides in the coming years, " he said.
Overall, the outlook among all is optimistic that preventative
maintenance technology can overcome the hurdles it faces.
" Ultimately, I can see this developing into a new maintenance
philosophy for aircraft. Right now, aircraft are maintained based
on MSG-3 philosophy. Which combines preventive maintenance on
certain systems and components with on-condition maintenance

on parts when failing. The evolution of this potentially enabled by
predictive maintenance is that most of the aircraft maintenance
will be driven based on monitored conditions of aircraft systems
and components. With those conditions either being monitored by
sensors or by machine learning models, " said de Bree.
" The use of predictive maintenance will continue to grow over
the coming years. Past data from customers over the last five years
shows that 45% of all parts removals were unexpected. The industry
was in real need for more intelligent predictions for maintenance
on AOG faults, remaining operating life and repetitive defects. IFS
Maintenix data now shows a machine learning approach to aircraft
analytics can lead to a 30% increase in uptime - key data when,
due to the current pandemic shut-down, airlines want to keep
costly AOG repairs to a minimum, " Elliott said.
" The area of predictive maintenance is something that is a significant technical improvement over the traditional monitoring and
trending analysis and we're all learning very quickly in the aviation
industry how hard it is to get the data. And we're all learning data
governance in terms of getting that data so that we can make really
efficient use of it. And it's exciting to be a part of all that and to be
a part of that growth and I'm just really excited about what the
next two to three years has in store for moving this technology
forward, " added Peterson.

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march2021

Table of Contents for the Digital Edition of march2021