In my previous blog I described how corrosion is a significant concern for defence aircraft, requiring frequent and costly inspections to stay alert to any environmental degradation. I also mentioned how the F-35 program uses our sensors and models in its Corrosion Prognostic Health Management (CPHM) system.
Let me start this blog from a slightly wider perspective.
To maintain the structural integrity of an aircraft, you need to manage two factors.
The first is fatigue, because metal becomes more susceptible to cracking with use. This phenomenon is well known, and has been managed with Health and Usage Monitoring Systems (HUMS) for many decades. We have a very successful HUMS programme in our Australian business with Classic Hornet, Super Hornet and Hawk.
The second factor is environmental degradation, which is where corrosion sits. A CPHM system is like a corrosion HUMS, and these are only just starting to be used in Australia.
In response to requests from Defence, as well as an awareness of the corrosion problems through our own maintenance activities, we developed our own CPHM system over the last seven years called ‘Environmental Degradation Monitoring and Prognostics’ (EDMAP).
Our system enables aircraft (and other platforms) to be smart structures, informing operators of the aircraft’s current and predicted condition, thus allowing maintenance to occur only when needed. This saves time and money, while improving aircraft availability.
This is usually where the skeptics start challenging that it’s impossible to accurately predict something as random as corrosion. I can see their point: in a fleet of aircraft, some will corrode faster than others despite the fact they are essentially operated and maintained in the same way, from the same airbase. Coupons of the same metal will corrode at different spots and rates even when exposed together inside an environmental chamber.
Our algorithms are world-leading, but we don’t have the capability to monitor and model all the parameters that lead to these results…yet.
The key is this - we don’t have to accurately predict corrosion to create a useful management tool. Let’s take HUMS as an example. Just like the variance seen in the onset of corrosion, fatigue cracking has substantial inconsistency too. HUMS doesn’t predict when structure will fail from fatigue, it uses safety margins and conservative assumptions in its models to give an early indication of when fatigue might be an issue.
Aircraft retired due to fatigue could probably be used for decades more, but we can’t accurately predict the exact failure point. A CPHM system employs the same philosophy with corrosion – with appropriate safety margins and conservative assumptions in its models, it can give an early indication of when corrosion might be an issue. Corrosion inspections are therefore unnecessary until that point.
What savings does this bring to the customer? Recently a corrosion inspection was deferred on a defence helicopter in Europe, based on the output of corrosion sensors. This single action saved US$250k.