Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) have long been sparking conversation around what the future of transport will look like. With recent major developments in the AAM sector, this is evolving from concept to imminent reality. Balkiz Sarihan, CEO & Head of UAM at Airbus shared her insights on this journey and what it could mean for our cities.

Firstly discussing the promise of AAM, Sarihan described what adding a new mobility layer to a city would look like and the potential it offers for revolutionising how we live our lives and design our cities.

The conversation also touched on the challenges that come with integrating this technology into the broader ecosystem, where Sarihan cautioned that patience and safety are paramount and fostering collaboration across stakeholders is essential.

Looking ahead, Sarihan unpacked the steps need to mature AAM aircraft, mentioning investment, safety standards, and user interface.

Questions asked:

• Can you briefly summarise the transformative potential of Advanced Air Mobility?
• What are the major challenges you foresee when it comes to the broader ecosystem of Urban Air Mobility? How are you pre-empting these?
• What are your priorities for the next five years?

Watch the full interview below.

For more 5 minute insights see:

• Willie Walsh: “They’re part of the problem, they’ve got to be part of the solution.”
• Unlocking MRO capacity through digitalisation with Karen Miller, GM, Connected Aero

The post Maturing AAM technology with CEO & Head of UAM at Airbus first appeared on Aerospace Tech Review.

Artificial intelligence (AI) is revolutionising every industry and aviation is no exception. Its transformative power already spans a multitude of applications and more doors are opening as the technology develops. However, its rapid integration into this safety critical sector requires a measured approach, facilitated by expert understanding of technology and the industry.

EUROCAE, the European Organisation for Civil Aviation Equipment, plays a pivotal role in advancing the aviation industry through its range of standards. The non-profit organisation brings together manufacturers, operators, regulators, and other aviation stakeholders to develop and promote standards for aviation equipment and related systems. Taking a proactive approach to standardisation, EUROCAE is instrumental in ensuring the aviation industry can harness the benefits of AI without compromising safety and trustworthiness.

Watch below for five-minute insights from Anna von Groote, Director General, EUROCAE on the importance of standardisation as the industry navigates the role of AI.

Questions asked include:

•  Can you articulate the impact AI has had on the industry? And how have you noticed this change in recent years?
• How do you tackle the issue of AI trustworthiness when thinking about safety within the industry?
• With AI evolving at such a rapid pace, how do you approach its standardisation and do you anticipate having to change this approach if its applications within the industry continue to proliferate?

See EUROCAE’s Video series on AI in aviation here. 

For more on AI see:

• Lufthansa Technik Philippines encourages startup-driven AI innovation for aircraft MRO
• Effective human-AI collaboration in the cockpit
• Industry 4.0: Digital Twin technology at Rolls-Royce

The post Ensuring safety while integrating AI with Anna von Groote, Director General, EUROCAE first appeared on Aerospace Tech Review.

At Aerospace Tech Week, Willie Walsh, Director General, The International Air Transport Association (IATA) joined for a five minute discussion on the industry landscape. During the interview, he outlined a path for tackling the sustainability challenge and looked at the failures of the Single European Sky (SES) deal.

Underscoring the critical role of sustainable aviation fuel (SAF) in navigating the decarbonisation of the industry, Walsh briefly mapped out the role governments must play in stimulating its scale up. Highlighting the concerning disparity between the US and European SAF production, Walsh cautioned that we are not seeing the right balance between incentives and mandates being adopted internationally, and governments are failing to recognise the opportunity in front of them.

Walsh urged that effectively addressing the sustainability challenge will take the support from every member of the ecosystem including governments, regulators, OEMs etc. Singling out fuel suppliers, Walsh said:

“Traditional fuel suppliers who have made hundreds of billions in profit off the industry over the years need to significantly accelerate their investment in the production of SAF […] They’re part of the problem, they’ve got to be part of the solution.”

Unpacking the flaws of the SES deal which Walsh previously condemned as a “failure,” he highlighted its initial promises: a tenfold improvement in safety, tripling Europe’s airspace capacity, substantial cost reduction, and a 10 per cent decrease in CO2 emissions. Criticising the deal for falling short on all four fronts, Walsh described the deal as “very disappointing given the critical importance of all of those issues.”

Questions asked:

• You described the EU’s Single European Sky deal as a failure. Which areas in particular did the agreement fall short and to what extent will this impact the industry’s ability to modernise European air traffic management?
• What do you see as the major challenges when it comes to meeting the net zero by 2050 goal and how many of these are going to require government involvement to overcome them?
• How do you propose we catalyse the mindset shift towards a more inclusive ecosystem involving governments, suppliers, airlines etc.?

Watch the full interview below.

For more video insights see:

• Disruptive sustainability technology with Grzegorz Ombach, Airbus
• From OCC to IOCC with Diederik-Jan Bos, Head of IOCC, SunExpress
• Driving aviation standards for emerging tech: EUROCAE’s role in safety, efficiency, and innovation

The post Willie Walsh: “They’re part of the problem, they’ve got to be part of the solution.” first appeared on Aerospace Tech Review.

The Airbus innovation arm UpNext has launched Optimate, a “flying truck” replicating an A350 cockpit. The fully-electric next-generation autonomy demonstrator emulates the aircraft, rolling down airport runways equipped with an A350 virtual flight deck and ‘computer vision’ devices, including geo-locating sensors, 4D radar and LIDAR, as well as a full flight test installation in the back to monitor the tests.

Developed in partnership with researchers, regulatory bodies, and industry stakeholders, Optimate is designed to both support pilots and increase operational safety. The truck has already been trialled at UpNext’s HQ and Blagnac airport but this year it aims to experience the runways of an international airport.

One key objective for the three-year research project is evaluating how a collaborative map and virtual flight assistant can aid a pilot’s strategic decisions alongside air traffic control and airline operations centres. A second objective is for the test bed to develop and test automatic taxiing grounded in reliable position calculations and unlocking the potential of quantum.

However, the press release detailed the project’s ultimate aim as “perform[ing] a highly efficient automatic ‘gate-to-gate’ mission on an Airbus commercial airliner, featuring 4D trajectory flight management, a tablet-operated connected virtual assistant, and overridable protections – all to support the flight crew.”

Remaining mindful of sustainability, the use of an electric vehicle reduces unnecessary CO2 emissions.

Michael Augello, CEO Airbus UpNext said:

“We are delighted to unveil another innovative demonstrator that reflects our unwavering commitment to pushing the boundaries of aviation. Our ambition is to use the best technologies to make our aircraft even more aware of their operating conditions, analysing it in as much detail as possible to become smart and reliable assistants to pilots, providing them with the optimal assistance. We are confident that this project will contribute to safer and more efficient air travel.”

For more on testing see:

• UK tests “ground-breaking” quantum enabled navigation systems
• “The future of air traffic control: ” Test centre built for Namur’s digital control tower
• Rolls-Royce tests its most powerful business aviation engine yet

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This month, the UK successfully tested “ground-breaking” quantum technology aimed at creating an unjammable back-up for GPS navigation systems.

Although the technology’s “practical implementation” in commercial aviation is still estimated to be 10-20 years away in the UK, this test signals a key milestone for quantum enabled navigation systems.

The research has received nearly £8m in funding from the UK government who are pushing to be seen as a world leader on quantum, and is the “first test of this type of technology in the UK on an aircraft in flight.”

Accordingly to the government press release, the test is part of a project funded by UK Research and Innovation (UKRI) specifically focusing on creating quantum sensors to address the UK’s heavy reliance on GNSS/GPS for location, navigation, and timing data.

Science Minister Andrew Griffith said:

“From passenger flights to shipping, we all depend on navigation systems that are accurate, safe and secure. The scientific research we are supporting here on quantum technology could well provide the resilience to protect our interests.”

The flight tests involved Infleqtion, a quantum information company, and aerospace companies BAE Systems and QinetiQ. The two tests showed the technology offers “exceptional accuracy, and resilience, independent of traditional satellite navigation using GPS.”

Roger McKinlay, Challenge Director Quantum Technologies at Innovate UK, part of UK Research and Innovation (UKRI), said:

“Modern infrastructure is increasingly dependent on highly accurate timing and navigation derived from satellite signals. These flight tests mark the culmination of two excellent projects which Infleqtion has had the vision to create and the deftness in leadership to execute with an outstanding team of collaborators.”

For more like this see:

• Combatting GNSS spoofing and jamming: EASA’s partnership with IATA

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Extensive labour shortages the aviation industry is currently facing have been identified as a critical challenge with the potential to slow progress, and the MRO sector is no exception. In fact, McKinsey & Company research indicates that by 2033, one-fifth of aviation maintenance technician jobs will go unfilled.

However, generative AI (gen AI) is seen as a potential way to bridge this growing gap, and the MRO industry is particularly is well positioned to benefit from the innovative technology. Gathering research on this topic, a recent McKinsey article looked at the transformative potential of gen AI for the MRO sector, here are some of its key insights.

The major ways gen AI can assist the MRO industry are as:

• Virtual AI maintenance and repair experts (“co-pilots”)
• AI-augmented reliability engineering tools
• Assistants who take care of busywork
• Permanent quality control supervisors
• Supply chain managers
• Accelerators of onboarding hires through skills training

Key challenges with its integration include:

• Striking the right balance between careful and agile
• Preserving strict safety and regulatory compliance
• Finding the right talent
• Having the right data

Highlighting gen AI’s potential, the article references a mining company that is scaling its support tools. The company is projected to see “at least a 35 per cent reduction in the time it will take technicians to troubleshoot equipment problems and at least a 25 per cent reduction in the time needed to do unplanned repairs.”

“Given the acute labour shortages in the MRO industry, these capabilities could turn out to be substantial productivity levers. There is also reason to believe that gen AI platforms could boost the quality, consistency, and accuracy of maintenance work, ultimately keeping more aircraft in the sky and minimizing aircraft out-of-service periods.”

Gen AI has the potential to transform the MRO sector, providing a range of solutions to the industry’s workforce challenge. Although its integration comes with a set of obstacles, if successful, the technology could help establish a more efficient, accurate, and safe industry.

For more about MRO see:

• KLM demonstrates how Apple Vision Pro can improve technical maintenance
• AI takes to the skies: The four practical applications of AI in aviation maintenance
• British Airways leverages real-time data to predict aircraft maintenance issues

The post McKinsey underscores gen AI’s role in bridging the labour gap first appeared on Aerospace Tech Review.

In 2026, air traffic at Charleroi and Liège airports will be remotely managed by a single digital control tower centre in based in Namur. The centre will oversee all ground movements during landing and take-off at the two airports.

Recently, SOWAER (Société Wallonne des Aéroports) and the Belgian air navigation service, skeyes, debuted the ‘Digital Tower Test Centre’ prototype at their site in Steenokkerzeel. The test centre is “almost identical” to the one currently being built in Namur and will be used to familiarise staff with the new technologies, train air traffic controllers, and deliver a seamless transition once the Namur centre is open. While the test centre is fed with real-time images from the masts in Liège and Charleroi, it does not have module for communicating with aircraft.

These digital towers are “the future for air traffic control,” using advanced cameras, infrared systems, and sensors at airports to receive real-time images on large screens at control centres showing a 360° view of the airport’s horizon. A ground radar system supplements this by pinpointing aircraft locations, even in poor weather. Augmented reality further enhances control by projecting extra information onto aircraft, aiding traffic management.

Eventually, the digital control centre in Namur will replace the physical towers at Charleroi and Liège airports. The innovative approach to air traffic control complements the wider digital transformations at the airports, illustrating their efforts to modernise infrastructure, streamline operations, and improve safety standards.

Image credit: skeyes

For more like this see:

From OCC to IOCC with Diederik-Jan Bos, Head of IOCC, SunExpress

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Korean Air has successfully completed the “world’s first” comprehensive urban air mobility (UAM) operations demonstration.

Partnering with Hyundai Motor Company, Korea Telecom (KT), Incheon International Airport Corporation (IIAC), and Hyundai Engineering & Construction, the South Korean flag carrier conducted five week demonstrations at Goheung Aviation Test Center in South Jeolla Province.

The urban air mobility (UAM) system relied on a 5G aviation communication network linking the electric vertical take-off and landing (e-VTOL) aircraft with the UAM operating systems. For the demonstrations, the airline conducted 10 different scenarios ranging from “normal to abnormal” during which they tested the functionality and performance of the operating systems.

Working to ensure safe UAM operations in high-density urban environments, the data collected from these tests will be analysed and the systems enhanced.

In a statement, the airline said:

“Korean Air will continue to engage in various UAM initiatives, and work to validate and enhance government-established UAM concepts and procedures to develop the UAM ecosystem in Korea.”

For more like this see:

• Panasonic Avionics Unveils Major Expansion to GEO Satellite Connectivity Network
• Connectivity Central to Modernization of Airspace Management
• Hughes JUPITER 3 Satellite Successfully Launches, Heralds New Era of Connectivity

The post Korean Air successfully tests 5G backed UAM system first appeared on Aerospace Tech Review.

Historically, augmented reality (AR) has opened up possibilities within the industry, especially around training and inspection. As the technology becomes more refined, its use cases evolve symbiotically. Recently, KLM Royal Dutch Airlines shared how they are using Apple’s Vision Pro to elevate technical maintenance and training.

In 2023, Apple debuted the Apple Vision Pro, “a revolutionary spatial computer that seamlessly blends digital content with the physical world.” With AR, users can overlay digital information and interactive elements onto their surroundings while virtual reality (VR) offers users a fully simulated and immersive digital experience.

Its debut restarted excitement around the potential use cases of extended reality (XR) across industries. This month, Apple showcased how KLM Royal Dutch Airlines is using the Vision Pro. The airline’s Engine Shop app allows technicians to see a step by step breakdown of the task ahead of them with detailed instructions overlayed on an accurate 3D model of the exact engine.

Bob Tulleken, Vice President of Operations Decision Support, KLM said:

“We see Apple Vision Pro as a tremendous value-add that will improve our fleet availability and operations […] Training our employees with spatial computing will lead to fewer costly errors because the most current information they need to do their job is there in front of them as they perform the task. This means we not only get vastly more efficient in our work, but also provide a better work environment for our employees to succeed.”

Apple shared this short video demonstrating how the airline is leveraging spatial computing for technical maintenance. Video credit: Apple.

The Apple Vision Pro may have re-ignited excitement around XR but the aviation industry has been leveraging immersive technologies that merge the physical and virtual worlds in a multitude of ways for some years. As the technology evolves, it will open doors to more applications across the industry giving way to transformative advancements.

The post KLM demonstrates how Apple Vision Pro can improve technical maintenance first appeared on Aerospace Tech Review.

AI is answering some of the most difficult questions in aviation.

I pose here four questions and show how AI is transforming aviation maintenance in four key areas:

1. Maintenance Scheduling & Supply Chain Optimization
2. Error Detection & Reclassification
3. Automated Failure, Troubleshooting, & Repair Identification
4. Predictive Maintenance & Anomaly Detection

I think maintenance can be a little more efficient, don’t you? Maintenance Scheduling & Supply Chain Optimization

An application of AI that has many use cases is optimization, which includes maintenance scheduling optimization.

An optimization engine that can schedule maintenance at the best possible time at the best possible location has the potential to greatly reduce maintenance costs and improve maintenance yield fleet wide. At the same time, optimizing the order that are performed in, and how personnel are assigned to tasks can result in more efficient maintenance—reducing costs, improving turnaround time, getting the aircraft back in the air sooner—thereby generating more revenue.

Are you sure that’s correct? Error Detection & Reclassification

Another use of AI is to identify errors made in entering data, or to reclassify data after the fact to ensure accuracy of data and improve the overall quality of the dataset. A common problem across the airline industry is the misclassification of the failed ATA system when raising a fault. These misclassifications can impact the data quality in the system.

IFS Customer Southwest Airlines has rolled out a solution to use AI to identify misclassified faults and improve the overall quality of their data. This is an excellent application of LLMs that learn to identify patterns in the text entered by the technicians to classify faults more accurately. Using AI to identify potential errors and surface those potential errors to a person helps to make the whole process vastly more efficient while maintaining authorized human oversight.

Let’s try this again—Automated Failure, Troubleshooting, and Repair Identification

When a fault is raised, a technician is often required to spend a considerable amount of time researching the correct source of a fault, what troubleshooting steps to take and what repairs to apply.

The logical extension of fault classification is to take the same kind of LLM model which will suggest potential sources of the failure, and recommend troubleshooting activities or even make repair suggestions. Suggestions would be based on previous success rates.

By providing first time fix rate percentages to the technician, they may choose options that save time by resolving the issue quicker, meaning the aircraft may be able to get back in the air sooner, or even prevent recurrences in the future. Avoiding or reducing has real value, according to Airlines for America, in 2023, delays have a direct cost of $101.18 for every minute a flight is delayed.

Now what will happen? Predictive Maintenance & Anomaly Detection

The concept of predictive maintenance is nothing new. However, what is new is the application of newer types of AI, namely Anomaly Detection and Pattern Recognition. Predictive maintenance uses time-series data—which is gathered over long periods of time recoded at fixed known points along the way, i.e., discrete data points in time.

Live feeds of sensor data changed that with IoT, allowing current data to be considered—but that huge amount of data is difficult to interpret, requiring highly trained data scientists. Then Machine Learning (ML) came into the picture. Using ML means that data scientists are now focussed on creating the current learning model for the AI, rather than developing the algorithm themselves.

Unsupervised learning models are lowering the barrier to entry for the use of AI in predictive maintenance applications. “Unsupervised” learning models for AI means that you can plug the AI into a set of data and it can figure out its own algorithm. This reduces the time and cost of implementing a solution, and also has the power to remove bias from the process, particularly when dealing with large amounts of unlabeled data like multiple terabytes of data points generated from a modern aircraft .

Anomaly Detection means that you can plug the AI into the sensor data to figure out what “normal” looks like, it then warns you whenever a deviation from “normal” occurs. Coupled with Pattern Recognition, the AI can learn to detect patterns in the sensor data that indicate certain events are about to occur—providing an early warning system that can warn what is about to happen with extremely accurate results.

AI is here to stay

By using AI to streamline tasks, to provide decision support to the human, to pare down the noise of information—while keeping the human in the loop, still requiring them to be the ultimate decision maker—cutting edge companies have the ability to make huge strides in terms of efficiency and accuracy.

These improvements can represent real value to airlines & air operators and ultimately, their customers.

Article by Rob Mather, Vice President, Aerospace and Defense Industries at IFS

The post AI takes to the skies: The four practical applications of AI in aviation maintenance first appeared on Aerospace Tech Review.