by   |    |  Estimated reading time: 6 minutes  |  in Aerospace & Defense, Business Agility, Business Technology, Digital Transformation   |  tagged ,

The aviation industry has been on an evolution to truly predictive maintenance for a number of years. Rolls-Royce continues to push engineering boundaries with its products and services by applying data science to deliver higher levels of aircraft availability for its customers, while as far back as the 1990’s, IFS Maintenix experts were involved in a U.S. Navy program to analyze engine component data to help predict failures.

Now, IFS Maintenix forms a core part of the Rolls-Royce Blue Data Thread initiative, supporting predictive maintenance for every life-limited component inside Rolls-Royce engines throughout their lifecycle—from during manufacturing through to operations and maintenance.

The Blue Data Thread program feeds into a wider vision for the future of Rolls-Royce aircraft engines, with the creation of the IntelligentEngine. “The IntelligentEngine combines the physical and digital worlds, by using digital twins to inform data-driven decisions to increase availability and minimize unexpected maintenance disruption,” explains Nick Ward, , VP Digital Systems, Rolls-Royce “The IntelligentEngine also reinforces the Rolls-Royce commitment to new power sources, such as electrification, for the long-term success of air travel and a focus on new innovations that matter to society’s future.”

Blue Data Thread allows airlines to pass the benefits to passengers

Unplanned maintenance is one of the main causes of aircraft on ground (AOG) delays. U.S. Bureau of Transportation statistics show in the last full year of uninterrupted airline operations, 2019, U.S. airlines reported 302 domestic tarmac delays longer than three hours, compared with 202 in 2018 and 193 in 2017.

Rolls-Royce has a fundamental mission that every Rolls-Royce powered aircraft flies on time, every time with an availability as close as possible to 100%. That works for the airlines that own the aircraft, Rolls-Royce as the OEM and passengers themselves. This is where the confluence of predictive maintenance incentives comes together for all parties involved in flying any given route.

The Blue Data Thread contributes significantly to the Rolls-Royce strategy to eliminate unplanned failures. A jet engine is an incredibly complex example of high-engineering but being in-tune with the specific maintenance requirements and performance allows Rolls-Royce to accomplish feats like powering an A330 to fly the equivalency of to the moon and back 50 times between overhauls.


IFS helps span the physical and digital spheres

Unlike some other OEM predictive maintenance initiatives, the Rolls-Royce Blue Data Thread is a two-way movement of data. The engine supplier is collecting data from multiple sources, such as engine health monitoring and information from airline maintenance management systems, contextual real time engine flying condition and other data sources including MRO data from Rolls-Royce engine facilities.

This is where IFS has provided strategic support on multiple levels. IFS Maintenix has automated the sharing of the data critical for Rolls-Royce to re-life its engine parts, but also took a broader scope to allow airlines and Rolls-Royce to collaborate and share much more information about the work which happens on their engines—for example which engine parts have been switched or inspected and even if any other aircraft systems have been impacted by engine behavior. The result of this two-way exchange is an even more complete picture of engine performance—a higher resolution digital twin and a way to deliver these digital insights to improve physical part use while in-service.

Added value – preventative maintenance measures are a thing of the past

Participating airlines were confidently expecting to see certain results from the Intelligent Engine and the Blue Data Thread initiatives in terms of overall engine performance and cost. However, what perhaps wasn’t anticipated was the weaving of new predictive maintenance results non-intrusively into day-to-day processes.

“A Rolls-Royce Trent engine can, on average, fly around the world over 1,000 times between significant engine events. Through multi-variable forecasting, IFS is able to map the data on how an airline expects to fly a particular engine and combine it with Rolls-Royce data on expected part life to provide a very accurate predictive maintenance deadline right down to individual part numbers,” continues Ward.

“Previously airlines may have spent weeks trying to piece together updated deadlines, but now accurate maintenance information is presented to airlines on a daily basis and is seamlessly consumed by their maintenance scheduling engine. Initial anecdotal reports show huge progress to extend the lifecycle of engines and components, increasing the time taken to first engine removal by 48 percent.

“This level of monitoring and data exchange is a step change in predictive maintenance. So many engine components and their details are being dynamically monitored that past traditional preventative maintenance approaches are a thing of the past. With this amount of tracking, most failures are detected on an individual level before they are likely to occur, well before planned maintenance cycles. Rolls-Royce has extreme faith in its predictive analytics strategy with a goal of zero false predictions and 100% success rate.”


More sustainable operations

More effective maintenance will also translate into sustainability benefits. As the aviation industry moves towards a greener future, digitalization and predictive maintenance is an important element for the engineering side of the industry and both IFS and Rolls-Royce have made strong sustainability commitments as part of their long-term business planning. The Blue Data Thread program aligns perfectly with these priorities. By reducing the need for maintenance interventions, part replacements and overhauls, manufacturing use of energy and resources is reduced and the emissions footprint of part and engine logistics is minimized.

Fast track deployment – but keep data control top of mind

From a technical perspective, airlines can be up and running on the Blue Data Thread through the IFS Maintenix plug-in in as little as two months. This requires a quick technology installation and is then a case of specifying key modelling information such as engine utilization. It’s the accessibility and sovereignty of data which can bring up potential roadblocks.

Airlines running other maintenance management systems need to make sure they can extract, store and analyze critical data profiles from their supporting software. Some airlines running legacy maintenance software on their aircraft may not be able to provide enough of the data required to feed the Blue Data Thread and a digital twin of their engine.

Those airlines that can, may have some data security reservations about certain lines of data, for example details around part leasing and ownership. This is why IFS and Rolls-Royce have designed the ability to give the airlines granular controls to manage the level of data lines specific for each airline taking part.

Underpinning the bilateral transfer of data from manufacturer to airline and back again is the need for an interface/dashboard to parse the aggregation of data points. The delta between data and information is the ability to translate raw data into actionable insights and meaningful information.

Flying towards a predictive and sustainable aviation future

With the Blue Data Thread, the tools and technology are now readily available to provide a consistent data backbone to underpin Rolls-Royce engines across airline fleets. This data exchange provides far more than simply health and maintenance information, it helps facilitate truly predictive maintenance to deliver fewer failures and allows airlines to maximize uptime and pass availability benefits onto the passengers they transport on a daily basis.

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One Response

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    Bret Bernhoft

    The idea of predictive maintenance is fascinating. It would seem that an artificial intelligence (of some kind) must be involved for this kind of technology to be possible? Anyhow, thank you for introducing me to some new concepts in this article, and for the time it took to put it together.


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