Yet, airlines continue to be among the first industries combining modern technology with classic industry. Simultaneously, Distributed Ledger Technologies (DLTs) and Artificial Intelligence (AI) are gaining traction across various industries, including aviation, where these technologies are being increasingly applied.

In this blog post we discuss DLT and AI use cases in the aviation industry. More specifically, we examine their potential in four areas: ground operations, customer-related activities, maintenance, repair, and overhaul activities (MRO), and airport infrastructure-related services. Figure 1 illustrates the four use cases.

Figure 1: Overview of the use cases to be discussed

Source: Swiss Economics

This blog post is structured as follows: First, we discuss why the aviation industry is a suitable candidate for innovative use cases of DLT and AI. Second, we explore the ways the above-mentioned four areas can benefit from these technologies and we also present existing implementations. Third, we conclude on our findings.

The aviation industry is a term including not only the airline industry but also aircraft manufacturers, research companies and military aviation. The airline industry includes all the businesses that provide or enable the air transportation of passengers and cargo. In this article, we are mainly focusing on the airline industry, but we might include a few examples and use cases from the whole aviation industry. The airline industry is a highly regulated, relatively rigid market with considerably large entry barriers, tight competition and a need for increasing efficiency and reducing costs. Even though global demand for airliners’ services is expected to double by 2040, high inflation rates, high jet fuel costs and increasingly tight labour markets put constant pressure on airliners’ operating costs (IATA, 2023).

Numerous facets within the industry provide ample opportunity for the implementation of DLT and AI applications.

It is a complex ecosystem of different actors and intermediaries, with a high level of trust required. These entities often need to exchange data among themselves, but certain data-sharing systems in use are outdated. DLT-applications can provide new solutions to the problem of sharing data in a trustless environment.

In numerous processes, errors or human misunderstandings are unacceptable due to the industry's stringent security standards. While many crucial processes are standardized to minimize complexity and expenses, several remain exceptionally intricate and reliant on human labour. Moreover, scarcity of resources like airport infrastructure and ground personnel, alongside unpredictable factors such as fluctuating weather conditions and demand, coupled with tight timelines, are typical hallmarks of an airport environment, significantly complicating efficient planning. In these scenarios, AI could be used not only to

automatize some standardized procedures, but also to enhance or even replace human decision-making by its ability to make predictions based on big data inputs (European Aviation High Level Group on AI, 2020).

Ground operations – track and trace

One of the potential areas, where DLT could be utilized is ground operations. According to a 2023 IATA report on Ground handling operations, there is considerable room for standardization. Post-Covid-19, ground handling has encountered challenges such as labour shortages, partly due to the extensive onboarding process for new staff. The IATA report emphasizes this concern, noting a surge in air travel demand following worldwide lockdowns, which escalates the risk of errors like baggage mishandling.

A potential solution to the rising problem of baggage mishandling could be provided by the traceability feature of blockchains. They could allow tracking of baggage from origin to target destination. Blockchain provides a common ledger for all airlines without the need to find a single entity that operates it. In addition, it allows a trusted database for customers to track their baggage. Moreover, through the power of smart contracts, any baggage that missed a flight could automatically be rebooked onto the next available flight to its destination. In 2022, bag delays during transfer accounted for 42% of all bag mishandling cases (SITA Baggage IT Insights report). The implementation of tracking systems and automation facilitated by blockchain could substantially reduce airlines' baggage claim- and labour costs and reduce customer dissatisfaction. Even though DLT has a large potential in this area, we could not find any verifiably DLT-based baggage track-and-trace implementation yet. However, a similar application exists in the cargo-industry. Freightchain allows the secure and tamper-proof booking of cargo space, tracking of shipments and the management of documentation with the power of blockchains.

Customer-related activities – trustless identity verification

The customer experience an airline provides determines satisfaction, which in turn increases the loyalty of passengers (Oliver, 1999). Airlines should therefore strive for the provision of a great airline experience. The overall customer experience during air travel is influenced by countless factors which cannot be directly controlled by the airlines but might still play an important role in the traveller’s perception of the airline (weather, ground operations’ service, airport services).

Nevertheless, there are a few areas where airlines can directly improve their services with the help of blockchain. Blockchain applications have a huge potential in the area of ticket sales, loyalty programs and passenger identification. During the Covid-19 pandemic, Air France introduced the ICC AOKpass, which is a blockchain-based health certification method. Similarly, IATA collaborated with Evernym to introduce its own blockchain-based platform, the IATA Travel Pass. The platform was also used by Emirates, Etihad, Qantas, Swiss, Singapore Airlines and British Airways. The need for a blockchain-based health

certificate arose from the need for a common framework for certification, authentication and secure saving of Covid-19 test results issued by local authorities and used in global air travel. The mentioned applications made the transfer and verification process more efficient and tackled privacy concerns.

Such a blockchain-based solution could be utilized not only with health certificates but also with other sensitive data, like passports. A prominent example of blockchain-based identity verification at airports is Zamna (formerly VChain Technology), which combines blockchain technology with facial recognition. Zamna’s goal is to eliminate the physical document checks at airports and automate the check-in process, massively benefitting customer experience during air travel. An automated and fast check-in and boarding process is not only beneficial for customers but would allow airlines and airports to reallocate their ground-personal to less manually repetitive tasks than putting a QR code under a scanner.

Maintenance, Repair and Overhaul (MRO) - anomaly detection

The maintenance, repair, and overhaul sector necessitates smooth collaboration among various entities within the confines of stringent regulatory standards concerning airworthiness and security, all while adhering to demanding time schedules. This complexity makes blockchain and AI technologies highly suitable for this sector.

Blockchain's capability to securely record and manage vast amounts of data while ensuring transparency and traceability aligns with the need for maintaining regulatory compliance and tracking the history of aircraft parts or maintenance records. AI's potential in predictive maintenance, anomaly detection, and optimizing workflows within tight timeframes complements the MRO sector's demands, facilitating proactive decision-making, reducing downtime, and enhancing overall operational efficiency. Hence, the integration of blockchain and AI technologies presents promising solutions for the MRO sector.

One of the potential problems blockchain technology can solve, is the elimination of counterfeit aircraft parts which could potentially compromise safety (Efthymiou et al. 2022). Another problem which a blockchain could solve is the safe storage of maintenance records, which when lost, can result in high costs. According to a PWC study from 2020, blockchain has the potential to decrease MRO costs in the industry by about 5% or USD 3.5 bn and increase industry revenue by USD 40bn. These estimates do not even include the whole aerospace and defence industry, which faces the same problem in the case of original equipment manufacturers (OEM), as the commercial aviation industry. As shown by Blockaviation, blockchain also allows the generation of a unified and integrated database of aircraft records. Keeping aircraft records safe and temper-proof is essential if an airline does not want to see the value of its fleet to rapidly diminish.

Machine learning algorithms could be trained on the datasets aggregated by blockchains, to provide timely forecasts on the parts that have to be replaced soon and thereby make the maintenance of aircrafts more cost-efficient (condition-based maintenance). Practical implementations of condition-based maintenance don't seem to be widely available yet [1]. However, a prominent Horizon 2020 research project used real-time operational data from KLM to prove that AI is capable of making accurate health predictions of aircraft systems and planning maintenance accordingly. A conclusion of the project was formulated by Paul Chün, VP of Technology Hub KLM Engineering & Maintenance, as follows:

„...condition-based maintenance has the potential to increase the up-time of high-value assets and transform unscheduled maintenance into scheduled maintenance. ... we can consider replacing the manual scheduling approach, typically limited to the next couple of days, by an automatic scheduling process that can consider several months in advance.”

The implications of the industry-wide implementation of such an AI solution in MRO would be immense and of a transformational nature to the whole maintenance procedures.

Airport infrastructure-related services

Airport infrastructure is considered to be scarce resources. Demand for airport infrastructure is managed by the allocation of landing- and take-off slots to each flight. Slots are defined as “permission given by a coordinator for a planned operation to use the full range of airport infrastructure necessary to arrive or depart at a Level 3 airport on a specific date and time”.

As the definition indicates, not all airports need to be managed through slots, only the Level 3 airports. According to the IATA, there were 205 level 3 airports worldwide in the Northern Summer Season of 2023. Slots are distributed among airlines twice a year on a dedicated IATA conference and according to the Worldwide Airport Slot Guidelines. Secondary trading of slots between airlines is allowed and can result in considerable slot prices (a pair of slots was sold by Air France-KLM to Oman Air for USD 75 Mio. in 2016).

Since according to the IATA rule, 80% of the slots must be used by an airline, otherwise they lose their slots, the system decreases airline flexibility and can lead to additional costs. These costs can occur for instance, if an airline operates a so-called ghost-flight (<10% of the flight is booked) just to be able to keep their assigned slot. This practice is also problematic from a sustainability aspect. Slot-leasing and selling could be potential solutions but might not always be feasible.

However, the complexity of processes and the number of different agents, that must coordinate before and after take-off, increases the risk of scheduling problems and resulting delays. Efficient slot-management benefits airlines, passengers and airspace regulators too. Also the EU sees the advantages of an automated and efficient slot management and therefore financially contributed to the SlotMachine project. The SlotMachine allowed airlines to swap slots such, that their sensitive data were preserved. This pilot project combined the power of AI with a distributed ledger. The biggest challenge that could be tackled, was to allow slot swapping between airlines, without the need of revealing their flight cost structures, which would otherwise lead to a competitive disadvantage. Facilitated slot swapping

also has the potential, to make the utilization of airport resources more efficient, which is otherwise a well-known problem in academic literature (see for example De Wit & Burghouwt, 2008 or Fukui, 2012). Furthermore, incentives to improve slot redistribution at the secondary markets can somewhat reduce the barriers to new entrants because otherwise slot allocation is greatly ruled by the principle of Grandfather rights [2]. The economic benefits are therefore undisputed.

Conclusion

To conclude, the aviation industry, known for its technological advancements and continuous pursuit of efficiency, is positioned at the forefront of innovation. This sector faces the pressing need for secure, transparent, and streamlined processes, compelling exploration into the potential of Distributed Ledger Technologies (DLTs) and Artificial Intelligence (AI). We discussed use cases in ground handling, customer related activities, MRO and airport infrastructure services. We find that the aviation sector is suitable for Blockchain, as it can support coordination among international companies in a complex environment. We identified track and trace of baggage and cargo to reduce information asymmetries; contactless identity verification of passengers to increase efficiency; the trade of illiquid assets, like airport slots to increase allocative efficiency, and tracking of records to preserve asset value. These use cases are potential areas for experimentations and implementations with blockchain. We furthermore identified AI to be able to reduce the need for human labour in the passenger identification procedures, in slot-swapping and in maintenance scheduling. AI can also reduce with its forecasting abilities the opportunity costs by decreasing downtime of aircraft due to maintenance.

These emerging technologies present promising solutions across various facets of aviation, including ground operations, customer-related activities, maintenance, repair, and overhaul (MRO), as well as airport infrastructure-related services.

Footnotes

[1]     Except a cooperation launched through SITA and ILS, in January 2023. https://www.sita.aero/stories/sita-stories/the-blockchain-partnership-revolutionizing-the-mro-sector/ [30.11.2023]

[2]     Grandfather rights stand for the practice that airlines, which kept a certain slot in the previous season are prioritized when the slots are being distributed in the primary market, therefore making it more difficult to new-entrants to get the specific slots and the number of slots they need for a profitable operation.

References

Air Cargo Next (2023). Blockchain platforms in air cargo. https://aircargonext.com/news/blockchain-platforms-in-air-cargo/ [04.12.2023]

Air France (2021). Air France and Groupe ADP extend the ICC AOKPass Solution test to flights to/from Paris-Charles de Gaulle, San Francisco and Los Angeles. https://corporate.airfrance.com/en/press-releases/air-france-and-groupe-adp-extend-icc-aokpass-solution-test-flights-tofrom-paris [17.11.2023]

Delft University of Technology (2022). More efficient aircraft maintenance through AI. https://www.tudelft.nl/en/2022/tu-delft/more-efficient-aircraft-maintenance-through-ai [30.11.2023]

De Wit, J.; & Burghouwt, G. (2008). Slot allocation and use at hub airports, perspectives for secondary trading. European Journal of Transport and Infrastructure Research, 8(2).

European Aviation High Level Group on AI. (2020). The FLY AI Report – Demystifying and Accelerating AI in Aviation/ATM; https://www.eurocontrol.int/sites/default/files/2020-03/eurocontrol-fly-ai-report-032020.pdf [10.11.2023]

European Commission. (2022). AI-powered flight allocation cuts costs and delays; https://cordis.europa.eu/article/id/442208-ai-powered-flight-allocation-cuts-costs-and-delays [29.11.2023]

Efthymiou, M.; McCarthy, K.; Markou, C.; & O’Connell, J. F. (2022). An Exploratory Research on Blockchain in Aviation: The Case of Maintenance, Repair and Overhaul (MRO) Organizations. Sustainability, 14(5).

Fukui, H. (2012). Do carriers abuse the slot system to inhibit airport capacity usage? Evidence from the US experience. Journal of Air Transport Management, 24, 1-6.

IATA – Global Outlook for Air Transport Report. (June 2023). https://www.iata.org/en/iata-repository/publications/economic-reports/global-outlook-for-air-transport----june-2023/ [10.11.2023]

IATA – Travel Pass (n.a.). https://airlines.iata.org/categories/topics/iata-travel-pass [29.11.2023]

International SOS (2020). First Use of a Digital Covid-19 Health Certificate to Cross an international Border Completed. https://www.internationalsos.com/newsroom/press-announcements/first-use-of-a-digital-covid19-health-certificate-to-cross-an-international-border-completed [17.11.2023]

Ledger Insights. (2021). Singapore, BA, Emirates, Etihad airlines trial blockchain Covid-19 credentials; https://www.ledgerinsights.com/singapore-ba-emirates-etihad-airlines-blockchain-covid-19-credentials-iata/ [29.11.2023]

Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63, 33-44. https://doi.org/10.1177/00222429990634s105

ReMAP (2022). ReMAP Results- Get to know what we’ve achieved. https://h2020-remap.eu/remap-results-get-to-know-what-weve-achieved/ [30.11.2023]

Schyga, J.; Hinckeldeyn, J.; Kreutzfeldt, J. (2019). Prototype for a permissioned blockchain in aircraft MRO. Berlin: epubli GmbH.

Sealy, R. P.; Gray, C.; Brady, G.; Thompson, S.; Denosky-Smart, M.; Lemasson, M. (2020). How blockchain can transform defence assets and give armed forces an advantage on the battlefield. PWC. https://www.pwc.com/gx/en/aerospace-defence/pdf/blockchain-defence.pdf [30.11.2023]

SITA. (2023). Baggage IT Insights. https://www.sita.aero/globalassets/docs/surveys--reports/2023-baggage-it-insights.pdf [04.12.2023]

Haben Sie Feedback oder Fragen? Bitte wenden Sie sich direkt per Mail an die Autorin oder liken/kommentieren/sharen Sie auf Linkedin.