98 million terabytes of data – that is what the OEMs, airlines and MRO service providers will have to grapple with, come 2026. This is the amount of data that is likely to be generated by the global fleet of commercial airlines, according to an Oliver Wyman MRO survey. Collating all this data and running analyses, aided by smart technology is the way forward for applying predictive engine maintenance and health monitoring systems in business processes of aviation companies.
All this load of engine sensor data, along with digital monitoring, artificial intelligence led big data analysis, use of cutting-edge technology like creation of Digital Twins (digital modelling of engines), are applied to achieve Predictive Engine Maintenance (PEM), or the ability to predict expensive and at times, critical failure before they occur.
Successful use of PEM is ultimately the ability to translate raw data into actionable insights based on meaningful information.
Digital Twins, Artificial Intelligence, IoT and more, are all the technologies in vogue that go into predictive engine maintenance management, making businesses processes more agile, adaptive and above all, allow businesses to remain viable. It is about gathering data, putting them through analytics, gaining key insights and making predictions about engine health and of course timely action taken.
For Rhonda Walthall, a Technical Fellow in Prognostics & Health Management at UTC Aerospace Systems, it is “Rather than being caught completely off-guard by maintenance requirements, predictive maintenance can offer you around a 15-day heads-up.”
Its little wonder then, that OEMs, Airlines and MROs have embraced PEM more than ever, for reaping benefits that a capital-intensive business requires, and these are:
- By using this predictive approach, engine MROs can address and avoid issues that are expensive, and likely to cause Aircraft on Ground situations
- PEM also allows aircraft owners/operators to set some of their maintenance cycles on actual needs rather than fixed time periods. In this way, substantial expenditure on maintenance is avoided, without compromising safety or aircraft availability.
Big industry players like OEMs and MRO providers like AFI KLM E & M, QOCO Systems and MTU Maintenance and similar, have all defined and refined their service offerings (using big data and cutting- edge technology) almost holistically, to benefit the entire industry.
What Do These Players Have on Offer
Since 2016, with their keen operational insights and data gleaned from aircraft engines, AFI KLM E&M have developed their own algorithms to provide advance warning of engine failures or of their components. They go on to provide relevant data to support engine health assessment to maximise engine ‘Time-on-Wing,’ according to Rik van Lieshout, Digital Products and Services Manager, at AFI KLM E & M. “AFI KLM E&M’s main focus is to create value for its 200 airline customers by maximizing fleet availability and asset value,” van Lieshout said.
MTU Maintenance on the other hand, is harnessing digital technology to effectively deliver PEM services that may be termed ‘prescriptive,’ based on data such as operational environments, derate, and engine performance. Accuracy in forecasting is achieved, concerning ‘on-wing time’ remaining for engines and as also optimal engine and unit removal time. MTU Maintenance’s full-scale performance analysis tool monitors and generates data pertaining to all engine parameters and a built-in alarm system that alerts users about engine conditions ahead of critical parameters’ exceedance.
The company’s ‘scrap rate prediction tools,’ based on engine and maintenance data, can predict default probabilities of high-cost material, according to Director of Industrial Engineering, Dr. Michael Bartlet.
QOCO Systems provides a data exchange platform that enables ‘bidirectional maintenance and engineering data flows between operators, OEMs, and analytics providers.’
QOCO Systems, contributes to the PEM concept in a different manner. The company focuses on, and propounds the idea of collaborating and sharing data. By this, airlines and OEMs can improve asset utilization making it mutually beneficial. Aircraft engines undergo extended time on-wing, planned maintenance schedules that are need-based, as also fewer and far between maintenance scheduling. The resultant benefits are leading to improved cost, and resource optimisation, efficiency and streamlined operations for the airline.
According to QOCO Systems’ Ville Santaniemi – Customer success Manager and Partner, “To maximize results, data sharing between airlines and PEM service providers is essential.”
PEM Trends & Benefits
PEM management is the engineering expertise linked to the knowledge of the operations that allows the interpretation of these data and information flows.
“We see a trend towards working with continuous data at higher sampling rates in order to cover critical operational conditions and manoeuvres,” says MTU’s Bartelt.
So, what benefits does Predictive Engine Maintenance (PEM) reap in:
- Minimizes time spent on shop visits
- Substantial cost savings
- Maximizing aircraft availability
- Prevents AOGs
- ‘Time on wing’ for engines may even double with advanced digitisation
- Save on compensation to passengers
- Avoid tarnishing brand reputation – operational reliability
PEM enables proactive analysis, instead of reactive analysis.
Says MTU Maintenance’s Bartlet, “we believe the next technology advancements in the MRO business will be driven by digitalization, and that is where the greatest development will take place across the industry.”
Look at Rolls Royce’s digital foray. The OEM uses AI forecasting to keep customers automatically informed to update their predicted maintenance deadlines for every engine component. This is Rolls Royce’s proprietary digital information thread connecting not only every Rolls-Royce powered aircraft, but covers every airline operation, maintenance shop, and factory.
Towards Democratization of Data
The full realisation of predictive maintenance depends on readily available big data shared throughout the industry- OEMs manufacturers, airlines, leasing companies, and similar entities. Essential is to have a sense of ownership, and a working environment where being collaborative about sharing the data, is encouraged.
As Micheál Armstrong, CEO of Armac Systems, opines that “We need to have almost a taxonomy around this data so that we can all agree and share and benefit from this data. That is almost a bigger challenge than the algorithms.”
The use of blockchain technology can democratise the data and protect people’s confidentiality at the same time. The moment data becomes proprietary, the plot is lost.
All aircraft and engine manufacturers today offer data tools as service products, and therefore it calls for a focus on developing tools to best analyse data,
According to Rhonda Walthall, Technical Fellow in Prognostics & Health Management at UTC Aerospace, “Stakeholders are coming together looking for opportunities to partner together and to share data yet still protect their intellectual property.” she says.
Some instances of commitment towards data sharing and collaboration are evident in Airbus’ Skywise open platform, set up in 2017 with the objective of combining data from Airbus’ in-service aircraft with airline and OEM data, in order to conduct in-depth analysis aimed at anticipating and optimising processes such as maintenance. According to Airbus, the company tripled the fleet covered by Skywise in just a little over one year – from 28 airlines with a total of 3500 aircraft to 100 airlines with a total of 10.000 aircraft under contract by the end of 2019.
Data sharing is likely to have a trickle-down effect on the rest of the supply chain, including logistics providers who can now access valuable insights and plan accordingly. In the future, the idea is to have a ‘digital thread throughout the lifecycle.’
Predictive maintenance is transforming the supply chain
Predictive maintenance for example can help determine the right moment to replace an engine part. This is critical because replacing too late can lead to unexpected failures, flight delays, cancellations, longer AOGs—not to mention, reduce asset availability.
Predictive Engine Maintenance and Positives for End-Customers
The end-customer is the air traveller who will spend on air travel, provided reliability and safety are assured. So how does Predictive Engine Maintenance impact the end-customer? For one, it can 1) Offer greater operational reliability, thus customers repose greater faith in a certain brand or airline company; 2) Delays and cancellations are less likely to plague customers; 3) Ensure greater safety for passengers; 4) When engines can be serviced, replaced, or overhauled before failure, airlines can dramatically reduce the risk of safety-related incidents.
Sustainability benefits
As the aviation industry moves towards a greener future, digitalisation and predictive maintenance are important elements for the engineering side of the industry. By reducing the need for maintenance schedule frequency, use of energy and resources is reduced, and the emissions footprint of engines and their parts’ logistics is minimized. PEM management plays its part in the sustainability story.
Conclusion
A risk-averse aviation industry has found a safe ground in PEM, making judicious use of digital tools, for performance enhancement and that of safety. At the same time be able to control huge costs by being prudent that predictive maintenance allows.
Looking into the future, it is believed that Predictive Engine Maintenance could well define how aircraft are designed, operated, and serviced in all aspects. making AOG situations an exception rather than a rule or a common occurrence.
Expert speak: Success will be achieved only with full data integration throughout the entire product lifecycle and the resultant improvement in predictability of engine performance.
Reference Credit:
AircraftIT.com
Satair.com
Avm-mag.com
