Sustainable operations in Aerospace industry

How can we optimise flight paths?

Optimizing flight paths has long been of interest to flight operators, partly because it combines improving sustainability with saving fuel, and thus money. Yet various studies show there is still plenty of room for reducing fuel use by flying more optimized paths. A 2021 study, for example, suggested New York to London flights could be up to 16.4% shorter. And distance is not the whole story; altitude, latitude, and atmospheric conditions all affect not just fuel use, but the impact that emissions have on the environment.

Whilst new propulsion and plane designs will take time, optimizing flight paths is something we can do right now. And the better we do it, the more time we buy for the net zero transition.

But even in a post-kerosene world, optimised flight plans will still matters. SAF planes will still produce high-altitude emissions. And it is hard to imagine completely carbon neutral hydrogen/electricity for a while, so the less energy needed, the better.

The low hanging fruit is to add environmental impact metrics into route planning and route tracking, to give a CO₂ equivalent figure. Taking all flights in an airspace together, we can then look to minimise CO₂ as well as flight times, delay risks, etc. We could then plan more effectively using this metric, and then retrospectively use the actual flight data to assess our effectiveness, to feed back into ever better planning. All the data we need to make a start on this exists today; we can do this now, with a few modifications to current systems.

As more data is collected, new sophisticated AI could be built to perform more complex analyses and fine tune routing algorithms to reduce impact further.

That would allow air traffic operators to choose the most sustainable route. A further step up would be for operators to collaborate on shared models to optimise for the whole flight, rather than just individual geographic airspaces.

Good route models will also help us make important future decisions. During the transition, which may be a decade or more, we will have a mix of clean and dirty planes in the sky. We will need to make complex decisions about routes – should we put the fossil fuel planes on the shortest paths to reduce their impact, or the clean planes on the shortest paths to incentivise their use? The exact mix will be a political decision, but good models help inform decisions and help airlines build business cases.

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Predictive maintenance

Another operational area for improving sustainability is maintenance of aircraft.

Predictive maintenance, already widely used, can ensure maintenance is scheduled at a convenient time and place, rather than having to divert planes, or fly out engineers. This is usually driven by cost saving and reducing downtime. But, as airlines look to reduce their emissions across the board, they should add ‘emissions reductions’ as a consideration shaping their predictive maintenance strategy.

Doing so may help them see things in new ways. For example, it may encourage them to explore the optimal global maintenance locations to reduce their overall footprint. Or to look at how technology can reduce emissions – for example our Andy3D platform let’s any technician put on VR headset and connect to a relevant expert anywhere in the world, who can guide them through the solution, thus removing the need to constantly fly a limited pool of specialists across the globe.

Airlines can also use predictive maintenance data to reduce their materials footprint. Many replacement schedules are based on historic data, with limited feedback loops. Parts designed to last 10,000 hours may be replaced after 1,000 to give suitable confidence levels. But with modern analysis techniques we can continually update models of lifetime failure with in-service data. This allows us to identify parts that can be swapped out less frequently without impacting confidence levels. A reduction in parts has a direct impact on the materials and energy required to produce service spares.

To make data-driven decisions about maintenance schedules which ensure optimal sustainability, we will need validated predictive maintenance tools, analysis of in-service maintenance data, and ongoing feedback loops. We need to be certain of what the data is telling us, and that it poses no compromise to safety. But once we are, there are big materials, transport, and personnel savings to be made.

Conclusion

Operations may not provide the big bang transformation of fuel transitions. But it provides many opportunities for optimisations that – if pursued at scale – will deliver meaningful emissions reductions, and cost savings. Importantly, many of these can be realized relatively quickly and without huge investment, leading to an impact now, and buying time for full decarbonisation of air travel.

These are all opportunities that are firmly within air traffic management providers, airlines, and airports control. They will therefore be easier to implement that the much talked of supply chain emissions reductions. Though these are also important, and we shall turn to these next.