NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking

Abstract

The paper presents a novel framework for implementing decentralized algorithms based on non-fungible tokens (NFTs) for digital twin management in aviation, with a focus on component lifecycle tracking. The proposed approach uses NFTs to create unique, immutable digital representations of physical aviation components capturing real-time records of a component’s entire lifecycle, from manufacture to retirement. This paper outlines detailed workflows for key processes, including part tracking, maintenance records, certification and compliance, supply chain management, flight logs, ownership and leasing, technical documentation, and quality assurance. This paper introduces a class of algorithms designed to manage the complex relationships between physical components, their digital twins, and associated NFTs. A unified model is presented to demonstrate how NFTs are created and updated across various stages of a component’s lifecycle, ensuring data integrity, regulatory compliance, and operational efficiency. This paper also discusses the architecture of the proposed system, exploring the relationships between data sources, digital twins, blockchain, NFTs, and other critical components. It further examines the main challenges of the NFT-based approach and outlines future research directions.

1. Introduction

1.1. Background and Motivation

The aviation industry depends on a diverse network of stakeholders to manage the lifecycle of aircraft components, ensuring that each part meets high standards for safety, quality, and regulatory compliance. These stakeholders—including suppliers, original equipment manufacturers (OEMs) [1], airlines, Continuing Airworthiness Management Organizations (CAMOs) [2], and maintenance, repair, and overhaul (MRO) providers [3]—each play a crucial role at various stages. However, the systems they use for component tracking are often fragmented, relying on isolated databases and sometimes even on paper-based records, leading to a lack of data integration and transparency [4,5].

Each stakeholder’s role contributes uniquely to component lifecycle management. Suppliers initiate the component lifecycle, assigning unique identifiers and certifications, yet their visibility into the component’s status diminishes once the part is distributed [6]. OEMs handle design, initial certification, and quality control, yet often lack direct access to data generated during later operational phases. Airlines, which are responsible for operational data and maintenance schedules, require real-time access to component information to minimize unplanned maintenance and downtime [7]. CAMOs ensure that the parts remain compliant with airworthiness standards, often struggling with limited data integration from other stakeholders [8]. Meanwhile, MRO providers rely on accurate records for inspections and repairs but face challenges in accessing a complete component history due to disjointed data-sharing practices [9]. This fragmentation complicates comprehensive component tracking, regulatory compliance, and overall operational efficiency, creating a need for an integrated solution that addresses the limitations of isolated systems.

Digital twin technology offers a solution by creating virtual models of physical assets, enabling stakeholders to monitor component conditions and simulate performance in real-time [10]. This approach supports predictive maintenance and helps reduce downtime by providing stakeholders with detailed insights into each asset’s current state [11]. However, digital twins alone do not provide the secure, unique, or immutable identities necessary for reliable tracking across multiple stakeholders [12], nor do they inherently ensure data integrity or prevent tampering, which is particularly important in the highly regulated and safety-critical aviation sector.

In this context, non-fungible tokens (NFTs) present a transformative approach that addresses these issues by establishing unique, blockchain-based digital identifiers for each component [13]. Unlike traditional identifiers, NFTs offer several specific advantages [14,15,16] that directly tackle the challenges of fragmentation and traceability in aviation component tracking.

First, each NFT serves as a permanent, unalterable record of a specific component’s lifecycle, from initial manufacturing through every maintenance, inspection, or operational update. Stored on a blockchain, these identifiers are immutable, meaning they cannot be changed or deleted, which helps create a tamper-proof record that all stakeholders can trust. The unique identity provided by each NFT ensures a reliable means of tracking the component across different stakeholders and systems, offering a consistent reference point across each phase of the component’s lifecycle.

Second, NFTs enhance the provenance and traceability of components. Each stakeholder can view a transparent, verifiable chain of custody, ensuring that a component’s complete history is accessible and up to date. For example, when an MRO provider services a part, or an airline installs it into an aircraft, the NFT’s record is updated to reflect these changes. This transparency minimizes the risk of counterfeit or uncertified parts entering the supply chain, as each NFT functions as a digital certificate of authenticity.

Third, NFTs integrate effectively with digital twins, thereby providing enhanced monitoring capabilities. Each NFT can be linked to a component’s digital twin, ensuring that the digital representation is associated with a verified physical asset. This linkage guarantees that all real-time operational data captured in the digital twin corresponds to a validated component, increasing both accuracy and trust. As a result, the combination of NFTs and digital twins enables stakeholders to monitor the state of each component accurately, using data that are verified and reflective of its real-world counterpart.

NFTs streamline compliance and regulatory auditing by securely recording every transaction, repair, or inspection associated with each component [17]. Regulatory authorities can access this blockchain record directly, simplifying the audit process and reducing administrative burdens on CAMOs and MROs. By replacing paper-based records with secure digital logs, NFTs support more efficient compliance management, as the verifiable record simplifies auditing and facilitates more streamlined compliance monitoring.

NFTs enable interoperability across diverse stakeholders and systems by creating a universal, blockchain-based ledger. Each stakeholder, irrespective of their internal system, can access the NFT as a consistent source of truth for component data, reducing delays due to data discrepancies. This shared access model promotes cross-stakeholder collaboration, which is often hampered by fragmented data practices, thus enabling better-informed decision-making and smoother operational processes.

The goal of this paper is to present a comprehensive framework that combines the capabilities of NFTs and digital twins to create a secure, traceable, and interoperable system for managing aviation component lifecycles.

1.2. Related Work

The concept of digital twins has emerged as an innovative approach that bridges the physical and digital worlds by creating virtual replicas of physical entities. These digital replicas are used to simulate, optimize, and predict various scenarios, resulting in enhanced efficiency and cost savings [18].

All major aviation companies have been actively developing platforms to predict component wear and optimize maintenance strategies. Some of the most significant advancements towards digital twins in the aviation sector include Aviatar (Lufthansa Technik, Hamburg, Germany) [19], Skywise (Airbus, Leiden, Netherlands) [20], Predix (General Electric, Boston, MA, USA) [21], PROGNOS (Air France Industries and KLM Engineering & Maintenance, Paris, France) [22], AnalytX (Boeing, Crystal City, VA, USA) [23], and others. These platforms represent significant strides in the integration of digital twin technologies within the aviation industry, but all of them have the problem of stakeholder borders, which restrict the platforms to gain the highest possible usage out of data.

The paper in [24] explores the implementation of digital twins (DTs) in the aviation industry, focusing on how these digital replicas of subsystems and processes can address specific, valuable use cases rather than providing holistic representations of entire systems. The study begins by summarizing common challenges in DT implementation across various industries, followed by an examination of specific characteristics of aircraft production. It then discusses various applications of DTs in different phases of the aircraft lifecycle, including production system development, logistics, quality assurance, and retrofitting, while also considering integration, organizational, and compliance challenges and opportunities within aircraft production and MRO.

The paper in [25] examines digital twins, focusing on their construction and utility across product lifecycles through the differentiation between master and shadow models. It highlights the need for digital twins to be specifically tailored to their intended added value or business functions, encompassing not only their data structures but also the communication technologies, processing methods, and interaction mechanisms utilized. In particular, the role of digital twins in MRO processes is emphasized, where they serve as monitoring systems, information sources, process managers, or repositories, ultimately acting as vital reservoirs of knowledge.

The work in [26] provides an introduction to the concept of a digital twin, a digital representation of a physical entity, and its growing significance in both academia and industry, particularly within aviation. It details the generation, development, and components of digital twins, and focuses on their application in the MRO of aircraft. The maintenance process and existing challenges are discussed, followed by a deeper dive into the application of digital twins in aircraft maintenance through system architecture and implementation perspectives. The chapter also presents three case studies demonstrating the digital twin’s utility in evaluating health status, predicting future health, and managing maintenance activities. It concludes with a summary and a review of the challenges in implementing digital twin technology in the aviation sector.

The study in [27] explores the challenges in maintaining consistent model-based data throughout the Product Lifecycle Management of aircraft cabins, which are high-value, customized consumer products facing rapidly changing market requirements. Due to the distributed nature of adaptations and modifications across multiple organizations, consistent data management is not guaranteed, leading to prolonged planning and increased ground-time during retrofits. The paper proposes the use of a digital twin to streamline the management of cabin data by maintaining an integrated, digital representation of 3D/2D as-is, as-designed, descriptive, and document-based data of the aircraft’s cabin and airframe structure. It further enhances the digital twin by automatically generating descriptive data and semantics, presenting a concept that not only preserves but also utilizes these data to significantly improve planning phases and retrofit processes.

Zaccaria et al. [28] introduced a comprehensive framework for monitoring, diagnostics, and health management across an aircraft fleet, utilizing a signature-based algorithm. The digital twin of the engine was used to replicate fault signatures for key components. Although the study primarily focused on a physics-based approach, the authors briefly explored the potential of incorporating neural network classifiers to enhance the system further. Yang et al. [29] concentrated on the turbofan disk, a critical component prone to crack failures. Their approach involved creating a digital surrogate of the disk using mathematical models and dynamic equations, employing a fully physics-based method that analyzed vibration response signals to detect cracks.

Wang et al. [30] emphasized the importance of integrating and fusing heterogeneous data sources to develop a life prediction method for aircraft structures. They incorporated material properties and structural geometry into a digital twin, constructed using finite element methods, specifically to simulate crack propagation. Chowdhury et al. [31] addressed the environmental control system of an aircraft, deploying a model-based solution directly on a real aircraft during ground testing to demonstrate the practical applicability of their work.

Ezhilarasu et al. [32] focused on health monitoring methods for aircraft electrical power systems. The digital twin of this network, integrated with other aircraft subsystems, was based on mathematical principles and well-established simulation tools. The data-driven aspect was represented by an artificial neural network developed for fault isolation and root cause prediction. In a follow-up paper [33], the authors introduced the FAVER framework, which uses digital twin concepts and reasoning techniques to identify, isolate, and predict faults across interacting aircraft subsystems. These use cases were demonstrated, showcasing a digital twin approach that combines both physics-based and data-driven modeling. This framework was further elaborated in a separate article [34], where three use cases were discussed, two of which relied on simulation models, while the third involved hardware-in-the-loop testing for more efficient results. The solutions applied in these studies used the open system architecture for condition-based monitoring, which enabled data manipulation algorithms and defined fault classification as part of the state detection and health assessment process.

Ramesh et al. [35] explored aircraft landing gear using an existing electric braking system model as the digital twin. By employing a physics-based approach within a software environment, they simulated specific fault types and incorporated a recurrent neural network to accurately identify these failures.

Huang et al. [36] offered a different approach to information fusion between physics-based and data-driven models, utilizing feed-forward and recurrent neural networks to develop an improved digital twin for real-time fault detection in aeroengines, specifically by constructing a degradation-adaptive correction model. Alvarez et al. [37] addressed the challenge of aircraft airspeed estimation in the event of a pitot tube sensor failure, proposing a solution that combined physics-based simulation models with data fusion and estimation techniques. Peng et al. [38] focused on the aeroengine, conducting practical tests in a test facility to validate their approach.

The paper in [39] introduces a comprehensive framework for integrating digital twins into aircraft lifecycle management, utilizing advanced technologies such as IoT sensors, big data analytics, machine learning, 6G communication, and cloud computing. It addresses the challenges of accurately creating digital twins during aircraft operations and maintenance, proposing solutions through emerging technologies.

Blockchain technology has emerged as a promising solution to tackle several challenges in the aviation maintenance, repair, and overhaul (MRO) industry. The MRO sector is characterized by its high complexity, involvement of multiple intermediaries, the need for data sharing among various stakeholders, and stringent security and regulatory requirements [40].

The paper [41] discusses the enhancement of traditional aircraft health monitoring systems by integrating artificial intelligence (AI) and blockchain technologies to address the complexity of modern aircraft systems and improve operational safety and efficiency.

In the MRO context, blockchain can be utilized to store and manage maintenance records, creating a tamper-proof and easily accessible history of aircraft and component maintenance [42]. This would help address critical issues such as counterfeit parts, which pose significant safety risks [43]. By ensuring the authenticity of components and creating a transparent and immutable ledger of maintenance activities, blockchain enhances safety and regulatory compliance within the aviation industry.

Furthermore, blockchain has the potential to streamline record-keeping processes, reducing paperwork, and improving the efficiency of data retrieval and sharing among stakeholders across the aviation ecosystem [44]. This technology could greatly enhance collaboration and trust between airlines, manufacturers, suppliers, and maintenance organizations, allowing for the more efficient management of records and improved traceability of parts and components.

Organizational readiness for blockchain adoption in MRO is a critical consideration [45]. The aviation industry is known for its cautious approach to adopting new technologies, given its stringent safety and regulatory requirements [46]. Blockchain implementation requires careful planning, industry collaboration, and regulatory support to ensure that it meets the aviation sector’s rigorous standards for safety and reliability.

Digital twin technology and NFTs have gained attention across numerous industries for their ability to enhance asset management, data integrity, and operational efficiency [47]. NFTs, initially popularized in the digital art and collectibles space, are increasingly being explored as solutions for asset verification and data authenticity across various domains [48]. In supply chain management, for instance, NFTs serve as digital certificates of authenticity for tracking the provenance of high-value goods, such as luxury items and pharmaceuticals, ensuring traceability and mitigating the risk of counterfeiting [49]. In the automotive industry, NFTs are being investigated for vehicle lifecycle management [50], where they could help track the history of individual components or vehicles, enhancing resale value and promoting transparency.

These general applications highlight the versatility and benefits of digital twins and NFTs across diverse industries, but the aviation sector presents unique challenges and constraints that amplify their value [51]. Aviation is characterized by low production volumes, highly regulated standards, and long lifecycle management requirements [52]. Aircraft components undergo stringent quality control and regulatory oversight, and each part must maintain a verifiable record of its history to ensure safety and compliance throughout its operational life [53]. Unlike other domains with high turnover or short asset lifespans, aviation components often remain in use for decades and are subject to numerous repairs, inspections, and replacements over time [54].

Given these characteristics, digital twins and NFTs offer a particularly promising solution for aviation. Digital twins enable real-time monitoring of components and allow for predictive insights, which are essential for proactive maintenance in a field where unplanned downtime carries high safety and financial costs [55,56]. Meanwhile, NFTs provide immutable, blockchain-based records that ensure each component’s history is preserved without risk of tampering or data loss—a crucial capability in an industry where data integrity is paramount for regulatory compliance and operational transparency.

In the field of asset lifecycle management, concepts such as digital twins, digital shadows, and digital threads are often discussed interchangeably. However, each term has a specific meaning and application, particularly in domains where real-time data accuracy and interoperability are critical factors [57]. Understanding these distinctions is essential to accurately evaluating existing works and the specific value that digital twins can bring to aviation.

A digital shadow refers to a representation of a physical asset that receives data updates from the asset, but the data flow is unidirectional—from the asset to the digital model [58]. This means that a digital shadow provides a snapshot of the asset’s current state based on recent data but does not enable any control or feedback from the digital representation to the physical asset [59]. Digital shadows are often used in monitoring systems where data integrity is important, but real-time interaction is not required [60].

A digital twin, on the other hand, represents a fully synchronized virtual model that not only mirrors the physical asset in real-time but also allows for bidirectional data flow, enabling interactions between the digital and physical entities [61]. In aviation, this means that digital twins of components or systems can be used not only to monitor real-time conditions and predict maintenance needs, but also to directly influence operations, make adjustments based on simulations, or inform maintenance scheduling dynamically [62]. The interactive nature of digital twins allows for more advanced predictive maintenance and operational optimization, which are crucial in highly regulated and safety-focused domains such as aviation [63].

A digital thread serves as a continuous chain of data and information that spans the entire lifecycle of an asset, from initial design to retirement [64]. It enables seamless data flow across all stages, departments, and stakeholders, creating a unified data structure [65]. In aviation, digital threads support lifecycle traceability, which is critical for regulatory compliance and safety [66].

By using these distinctions, we can see that many existing works referenced in this paper fall under the category of digital shadows, as they focus primarily on data collection and monitoring without enabling bidirectional interaction or predictive control. However, true digital twin applications in aviation, such as those deployed by Airbus Skywise [20] and Lufthansa Technik Aviatar [19], demonstrate the potential of interactive digital models to drive real-time decision-making and operational efficiencies. This paper adopts a digital twin perspective, emphasizing the need for interactive, synchronized models in component lifecycle management, while recognizing the complementary roles that digital shadows and digital threads can play in a comprehensive digital ecosystem.

In this paper, digital twin technology refers to a comprehensive framework encompassing the architecture, interfaces, and guiding philosophy for creating and managing digital replicas of physical aviation components. Together, these elements provide a robust, interactive platform that ensures traceability, real-time monitoring, and lifecycle optimization of aviation components, meeting the industry’s high standards for safety, reliability, and operational efficiency.

1.3. Research Gap, Contributions and Paper Structure

Although existing research has made strides in integrating digital twin technology with data-driven models, several gaps remain, particularly in aviation component management. The current literature primarily emphasizes either physics-based models or data fusion methods, without fully harnessing the potential of blockchain and NFT-based frameworks to ensure traceability and data security throughout the lifecycle of aviation components. Additionally, there is limited exploration of how NFTs can be used for dynamic, real-time updates of digital twins across multiple operational stages, including compliance, supply chain management, and predictive maintenance.

In supply chain management, NFTs provide a secure, immutable digital record for each component, capturing key data points from manufacturing through distribution to installation. This transparency enables all stakeholders to verify a component’s authenticity and trace its lifecycle, reducing risks of counterfeit parts, improving inventory accuracy, and enhancing the efficiency of part tracking and provenance throughout the supply chain. For Predictive Maintenance, NFTs can integrate real-time operational data from components, which allows maintenance teams to assess performance and wear levels based on verified historical records. By coupling NFTs with data-driven insights from digital twins, this approach enables early identification of potential faults, more accurate maintenance scheduling, and minimized unplanned downtimes. This streamlined, secure flow of verified data enhances the precision and reliability of maintenance decisions, optimizing component lifespan and availability.

This paper aims to bridge these gaps by proposing an NFT-based framework for digital twin management that uses the unique properties of blockchain to offer a secure, transparent, and immutable system for component lifecycle tracking. Through this approach, we address the challenges of system scalability, data integration, and regulatory compliance in aviation, presenting a holistic solution that combines advanced algorithms with decentralized technology.

The structure of this paper is organized as follows. Section 2 introduces the foundational concepts of the NFT-based digital twin ecosystem and explores its application to aviation components, emphasizing the integration of blockchain technology. Section 3 delves into the algorithms and workflows developed for managing the lifecycle of aviation components, covering areas such as part tracking, maintenance records, certification, supply chain logistics, and flight logs. In Section 4, the architecture of the proposed NFT-based system is examined, with a focus on critical elements, such as smart contracts, decentralized storage, and the integration of blockchain with existing aviation infrastructure. Section 5 provides an analysis of the benefits and challenges of implementing NFT-based frameworks in aviation, as well as outlining potential future research directions. Section 4.7 presents the conclusions, summarizing this study’s contributions to advancing secure, efficient, and transparent lifecycle management of aviation components using NFT and blockchain technologies.

All figures presented in this paper are original and created by the author to illustrate key concepts and frameworks discussed throughout this study. These figures are not adapted or reproduced from other sources.

2. NTF-Based Digital Twin Ecosystem in Aviation Industry

The integration of non-fungible tokens into the aviation industry represents a paradigm shift in how we approach data management, security, and operational efficiency in aviation. This innovative approach promises to transform how aircraft, their components, and related processes that are managed throughout their lifecycle, offering unprecedented levels of transparency, efficiency, and security. The concept is based on the digital twin ecosystem and the framework of applications using NFTs, which are discussed in this section of the article.

2.1. Structure of NTF-Based Digital Twin Ecosystem

The aviation digital twin ecosystem (DTE) based on NFTs creates a comprehensive digital representation of physical aviation assets, enabling levels of tracking, analysis, and management throughout the entire lifecycle of aircraft and their components (Figure 1). It covers the granular component-level tokenization, the integration at the aircraft level, real-time updates, blockchain-based verification, smart contract integration, supply chain integration, data analytics and predictive maintenance capabilities, regulatory compliance aspects, end-of-life management, and the importance of interoperability and standards.

Figure 1 illustrates a multi-layered framework for managing aviation component lifecycles through distinct functional levels. The physical layer (Level 1) represents the actual physical assets, including the aircraft and its components. These are connected to the digital representation layer (Level 2), where each physical component and the aircraft are mirrored by digital models—specifically, digital twins for real-time monitoring and NFTs for immutable, blockchain-based identity and tracking. Moving up to the operational layer (Level 3), the digital representations facilitate various operational functions, such as maintenance management, supply chain integration, performance monitoring, and data analytics, enabling proactive decision-making and streamlined operations. The topmost layer, the management and compliance layer (Level 4), encompasses overarching regulatory compliance, data management, and security protocols that ensure the integrity and safety of the entire system. This layered structure integrates physical assets with digital technologies, operational processes, and compliance frameworks to create a cohesive, traceable, and secure lifecycle management system.

At the heart of this ecosystem lies the concept of digital twins—virtual representations of physical assets. In this context, each aircraft is assigned a unique NFT that serves as its digital counterpart. This aircraft-level NFT is not a static entity but a dynamic, evolving digital asset that continuously updates to reflect the current state, configuration, and history of the physical aircraft it represents. The aircraft NFT is composed of multiple component NFTs, each representing a critical part of the plane, such as engines, avionics systems, or structural elements. These component NFTs contain detailed information, including manufacturer details, production date, technical specifications, and ongoing operational data.

The creation of these digital twins begins at the manufacturing stage. As each component is produced, the manufacturer generates a corresponding NFT, embedding it with initial data, such as production specifications, compliance certifications, and unique identifiers. As these components move through the supply chain, their NFTs are updated by suppliers and distributors, creating an unbroken chain of custody and provenance. When components are integrated into an aircraft, their individual NFTs become part of the larger aircraft NFT, forming a comprehensive digital representation of the entire vessel.

Once an aircraft enters service, its digital twin comes alive with real-time data. Every flight, maintenance action, and performance metric are recorded and linked to the relevant NFTs. This constant stream of information creates a living, breathing digital entity that accurately reflects the current state and history of the physical aircraft. Airlines and operators interact with these NFTs, updating them with operational data, while maintenance providers record their actions, ensuring a complete and accurate maintenance history.

The backbone of this ecosystem is blockchain technology. All updates and transactions involving the NFTs are recorded on a distributed ledger, ensuring the immutability and traceability of all data. This blockchain-based approach prevents fraudulent activities, data manipulation, and provides a single source of truth for all stakeholders. The decentralized nature of blockchain also enhances data security and resilience, which are crucial factors in the highly regulated aviation industry.

Smart contracts, self-executing code on the blockchain, play a pivotal role in automating various processes within the ecosystem. These contracts can trigger maintenance alerts based on usage metrics, update certification statuses, manage access rights to technical data, and even facilitate ownership or lease transfers. By automating these processes, smart contracts reduce human error, increase efficiency, and ensure compliance with predefined rules and regulations.

The rich, real-time data provided by this DTE enables advanced analytics and predictive maintenance capabilities. By analyzing the vast amount of data collected across multiple aircraft and components, airlines and maintenance providers can identify patterns, predict potential issues before they occur, and optimize their operations. This data-driven approach not only enhances safety but also has the potential to significantly reduce maintenance costs and aircraft downtime.

Regulatory compliance, a critical aspect of aviation, is streamlined within this ecosystem. Regulatory authorities can have direct, permissioned access to relevant NFT data, allowing for more efficient audits and inspections. The immutable nature of blockchain ensures that all records are tamper-proof, providing a reliable audit trail. Compliance checks can be automated through smart contracts, alerting stakeholders to any deviations from regulatory requirements.

As aircraft and components reach the end of their operational life, the DTE continues to provide value. The complete history contained within the NFTs facilitates efficient and compliant decommissioning processes. Recycling and disposal activities are recorded, ensuring adherence to environmental regulations. Even after a physical asset is retired, its digital twin remains as a permanent, accessible record.

2.2. A Comprehensive Framework of NFT Applications in Aviation

The integration of NFTs into the aviation industry presents a groundbreaking framework that promises to change key aspects of aircraft management, maintenance, and operations. This innovative approach uses blockchain technology to create a secure, transparent, and efficient ecosystem across eight critical areas of aviation (Figure 2).

At the heart of this framework is the concept of digital twins for aircraft parts. Each component is assigned a unique NFT, serving as its digital counterpart and containing its entire lifecycle information. This application enables unprecedented traceability and informed decision-making in maintenance and fleet management. Complementing this, maintenance records are transformed into tamper-proof digital logs, with each activity recorded as an NFT. This ensures the integrity of maintenance history, enhances transparency, and simplifies auditing processes.

The framework extends to personnel management through NFT-based certifications for pilots, mechanics, and other aviation professionals. These digital credentials are easily verifiable and secure, streamlining the certification process and reducing the risk of fraud. In the realm of supply chain management, NFTs track the provenance of aircraft parts, creating a verifiable chain of custody that significantly reduces the risk of counterfeit parts entering the system.

Operational data are captured through flight log NFTs, each representing a unique flight and containing comprehensive information such as route, duration, crew details, and performance data. This creates an immutable record of an aircraft’s operational history, facilitating more accurate tracking and analysis. Ownership and leasing rights are also represented by NFTs, simplifying transfers and providing a clear chain of custody for aircraft.

Technical documentation management is revolutionized by linking critical documents to NFTs, ensuring access to the most current versions and controlling distribution to authorized personnel. This significantly reduces the risk of using outdated information in aircraft maintenance and operations. Lastly, the framework incorporates quality assurance processes, with NFTs tracking inspections and tests, thereby enhancing accountability and facilitating easier identification of quality trends or issues.

This comprehensive NFT framework in aviation addresses critical aspects of the industry, from granular part tracking to overarching quality assurance processes. By using blockchain technology, it offers a new paradigm in aviation management that promises enhanced safety, efficiency, and transparency.

In Section 3, we will consider the algorithms for using the applications specified in the framework in detail.

2.3. Architecture of NFT-Based System for Aviation Applications

The architecture in Figure 3 illustrates a comprehensive NFT-based system for aviation applications, seamlessly integrating blockchain technology with existing aviation infrastructure.

At the top level, a user interface provides the entry point for users to interact with the system. This is supported by an identity and access management component, ensuring secure authentication and authorization for all users and system elements. An application programming interface (API) gateway manages and routes external requests to appropriate services within the system.

The central application layer acts as the core, orchestrating data flow and operations between various components. It connects to several key elements: cloud infrastructure, which includes off-chain storage for handling large datasets unsuitable for blockchain; a blockchain layer, housing smart contracts for automating rules and agreements, and NFT tokens representing unique digital aviation assets such as aircraft parts, maintenance records, or flight logs; and an integration layer that facilitates communication with external systems.

The blockchain layer is particularly significant, using the immutability and transparency of blockchain technology to enhance trust and efficiency in aviation processes. Smart contracts can automate complex procedures such as maintenance scheduling or parts tracking, while NFTs provide a secure, verifiable method for digitally representing and transferring ownership of aviation assets.

The integration layer plays a crucial role in connecting the blockchain system with legacy systems, specifically existing aviation systems. This ensures seamless data flow and interoperability between the new blockchain-based platform and current aviation infrastructure, allowing for gradual adoption and minimizing disruption to existing operations.

This architecture is designed to address specific challenges in the aviation industry, such as supply chain management, maintenance tracking, and regulatory compliance. By combining blockchain’s security and transparency with the NFT’s unique asset representation capabilities, the system offers a robust platform for modernizing aviation operations, enhancing safety, and improving efficiency across the industry.

3. Results

This section presents the results of applying the NFT-based framework to various critical processes within aviation component lifecycle management. The proposed system integrates blockchain technology, digital twins, and smart contracts to create a comprehensive and transparent record of every stage in the lifecycle of aircraft components. This section focuses on outlining the specific workflows that demonstrate the system’s ability to track, manage, and update the digital representations of physical components in real time. These workflows cover key areas of the framework (Figure 2), such as aircraft part tracking, maintenance record management, certification and compliance, supply chain management, flight logs, and ownership and leasing procedures. Each workflow illustrates how NFTs can provide secure, immutable, and verifiable data, ultimately contributing to enhanced operational efficiency and regulatory compliance within the aviation industry.

3.1. Methodology for Workflow Development

The workflows presented in this chapter are derived from a synthesis of theoretical research, established aviation practices, and industry-standard frameworks for component lifecycle management. Our approach involved an in-depth review of the current processes used in MRO, as well as asset tracking and compliance within the aviation industry. Additionally, we examined existing literature on digital twins and NFTs to explore how these technologies could address specific challenges associated with data integrity, traceability, and operational efficiency.

These workflows were designed to model realistic scenarios in aviation component management, simulating typical lifecycle stages, such as manufacturing, certification, installation, in-service monitoring, maintenance, and retirement. We used industry-standard terminology and structured each workflow to align with common processes used by stakeholders such as airlines, OEMs, CAMOs, and MRO providers. By doing so, we aimed to ensure semantic coherence and practical relevance for real-world aviation operations.

This methodology allowed us to construct workflows that are both theoretically robust and aligned with the practical needs of the aviation industry. Each workflow is intended to demonstrate how digital twins and NFTs can be integrated into existing aviation processes to enhance lifecycle management, regulatory compliance, and predictive maintenance capabilities.

3.2. The Workflow for Aircraft Parts Tracking Using NTF-Based Technology

The workflow for aircraft parts tracking, as depicted in the flowchart in Figure 4, illustrates a comprehensive lifecycle management system utilizing NFT technology.

This process begins at the manufacturing stage, where each individual aircraft part is produced. Immediately following production, a unique NFT is created for the part, serving as its digital representation and establishing the foundation for its traceable history.

The part then undergoes initial certification, a critical step to ensure it meets all required standards and specifications. This certification information is recorded by updating the associated NFT, creating an immutable record of the part’s validated quality and compliance. Once certified, the part moves into inventory, with its NFT again being updated to reflect its storage location and availability status.

When the part is selected for use, it enters the installation phase. The NFT is updated to record details of its installation, including the specific aircraft it is fitted to and the date of installation. This marks the transition of the part into active service.

The in-service stage is where the part spends most of its operational life. During this phase, the NFT plays a crucial role in ongoing management. It receives periodic updates to record flight hours, operating conditions, and any notable events. If the part requires maintenance, it temporarily leaves the in-service status. The maintenance process involves inspections, repairs, or overhauls as needed, with each action meticulously documented through updates to the NFT.

Following maintenance, the part undergoes a status check. This evaluation determines whether the part is still serviceable. If deemed serviceable, it returns to in-service status, with the NFT updated to reflect its renewed condition and any maintenance performed. The NFT’s historical data help inform decisions about the part’s continued airworthiness and suitability for further use.

If a part is found to be unserviceable during the status check, or if it reaches the end of its operational lifespan, it moves to the retirement phase. The NFT is updated one final time to record the retirement, including the reason and date, effectively closing the digital record of the part’s lifecycle.

3.3. The Workflow for Maintenance Records Using NTF-Based Technology

The workflow for maintenance records using an NFT-based system presents a technologically advanced approach to aircraft maintenance documentation and tracking (Figure 5). This process integrates regulatory compliance, detailed inspections, and quality checks, while using NFTs to ensure secure, immutable record-keeping throughout the maintenance lifecycle.

The process begins when maintenance is scheduled for an aircraft or its components. At this point, a new NFT is created to represent this specific maintenance event. This digital token will serve as a unique, blockchain-based record of all activities and outcomes related to this maintenance session.

The first operational step is the pre-maintenance inspection. During this phase, technicians thoroughly examine the aircraft or component to assess its condition and identify any issues that need addressing. The findings from this inspection are recorded, and the NFT is updated accordingly, creating a baseline for the maintenance work to follow.

As the workflow progresses to the maintenance performed stage, all actions, replacements, and repairs are meticulously documented. Each step of the maintenance process is recorded, and the NFT is continually updated to reflect these activities. This ensures a comprehensive, real-time record of all work carried out.

Following the completion of maintenance tasks, a post-maintenance inspection is conducted. This crucial step verifies that all required work has been performed correctly, and that the aircraft or component meets all necessary standards. The results of this inspection are also recorded, with the NFT being updated to reflect the outcomes.

A quality check follows the post-maintenance inspection. This serves as a final verification that all work meets the required quality standards. If the maintenance passes this check, the process moves to sign-off and approval. If issues are identified, the workflow directs to an address issues stage, where any problems are rectified before the maintenance can be approved.

Throughout these stages, there is a continuous emphasis on regulatory compliance. The system verifies compliance at multiple points in the process, ensuring that all maintenance activities adhere to relevant aviation regulations and standards.

Once all checks are passed and issues (if any) are addressed, the maintenance undergoes a final sign-off and approval. This step typically involves authorized personnel reviewing all the documented work and inspections before giving final approval. The NFT is updated to reflect this approval, creating an indelible record of the maintenance event’s successful completion.

After approval, the aircraft or component returns to service. The NFT is updated once more to indicate this change in status. Following this, the aircraft records are updated to reflect the completed maintenance. This step ensures that the broader aircraft documentation is in sync with the specific maintenance event.

The final stages involve linking the maintenance NFT with other relevant NFTs. This creates a network of interconnected digital records, allowing for comprehensive tracking of the aircraft’s maintenance history and the status of its various parts.

3.4. The Workflow for Certification and Compliance Using NTF-Based Technology

The workflow for certification and compliance using an NFT-based system outlines a comprehensive process that ensures that rigorous standards are met while maintaining a secure and immutable record of all stages (Figure 6) to create a transparent, traceable, and tamper-resistant documentation trail throughout the certification lifecycle.

The process begins with an application for certification. At this point, a unique NFT is created to represent the entire certification journey. This digital token will serve as the primary record, updated at each stage to reflect the current status and history of the certification process.

Following the application, an initial assessment is conducted. The results of this assessment are recorded by updating the NFT, creating the first substantial entry in the certification record. This stage culminates in a critical decision point: determining whether the subject meets the necessary requirements.

If the requirements are not met, the process moves to address deficiencies. Here, any issues identified during the initial assessment are tackled. The NFT is updated to reflect these corrective actions, maintaining a clear record of the improvements made. Once deficiencies are addressed, the process loops back to the initial assessment stage for re-evaluation.

When the requirements are met, the process advances to evaluation and testing. This more intensive phase involves thorough examinations and practical tests to ensure full compliance with certification standards. The NFT is updated with detailed results of these evaluations, providing a comprehensive record of performance across various criteria.

Another decision point follows, determining whether the subject passed the evaluation and testing phases. If not, additional training or corrections are required. This stage allows for targeted improvements based on specific shortcomings identified during evaluation. The NFT is updated to reflect these additional measures, ensuring a complete record of all steps taken towards certification.

Upon successful completion of evaluation and testing, the certification is issued. This milestone is recorded in the NFT, marking a significant transition in the subject’s status. The certification then becomes active, with the NFT serving as the authoritative digital representation of this certified status.

During the period of active certification, two parallel processes occur:

• Ongoing compliance monitoring, which involves regular checks and updates to ensure continued adherence to standards. The NFT is periodically updated with compliance data, creating a real-time record of the subject’s status.
• Tracking of certification expiration, during which the system monitors the validity period of the certification. As expiration approaches, it triggers the recertification process, ensuring timely renewal of credentials.

The final decision point in the workflow asks whether compliance is maintained. If yes, the certification remains active, and the cycle of monitoring and potential recertification continues. If compliance falters, the process may lead to suspension or revocation of the certification. This severe action would be recorded in the NFT, providing an indelible record of the certification’s termination and the reasons behind it.

3.5. The Workflow for Supply Chain Management Using NTF-Based Technology

The workflow for supply chain management using an NFT-based system presents an innovative approach to tracking aircraft parts throughout their lifecycle (Figure 7) to create a secure, transparent, and immutable record of each part’s journey from manufacture to retirement.

The process begins with part manufacturing. At this crucial initial stage, a unique NFT is created for each individual part. This digital token serves as the part’s digital twin, containing all relevant information and acting as a secure, blockchain-based record of the part’s entire history.

Following manufacture, the part undergoes quality control. The results of these quality checks are recorded by updating the NFT, ensuring that the part’s quality status is permanently logged. This step is vital for maintaining high safety standards in the aviation industry.

The next stage is certification, where the part receives necessary approvals and certifications. Again, the NFT is updated to reflect this critical information, creating an indelible record of the part’s compliance with industry standards and regulations.

Once certified, the part moves to warehouse storage. The NFT is updated with location data and storage conditions, facilitating efficient inventory management and traceability.

When a part is needed, it enters the order fulfillment stage. The NFT is updated to reflect that the part has been allocated to a specific order, enhancing supply chain visibility.

The shipping stage follows, where the NFT is updated with shipping details, including carrier information and expected delivery dates. This allows for the real-time tracking of the part’s movement through the supply chain.

Upon arrival at its destination, the receiving process occurs. The NFT is updated to confirm receipt, including date, time, and the condition of the part upon arrival.

Next, the part undergoes inspection. The results of this inspection are recorded in the NFT, maintaining a clear record of the part’s condition at each stage of its journey.

A critical decision point follows: “Passes inspection?” If the part passes, it moves to inventory, and the NFT is updated accordingly. If it fails, the part is returned to the supplier, with the NFT recording this rejection and return process.

From inventory, the part proceeds to installation. The NFT is updated with installation details, including the specific aircraft and location where the part is installed.

Once installed, the part enters the in-service tracking phase. Here, the NFT is continually updated with usage data, performance metrics, and any issues encountered during operation.

During the in-service tracking, there is an ongoing assessment: “Maintenance required?” If maintenance is needed, the part enters the maintenance stage, and the NFT is updated with details of the maintenance performed. After maintenance, the part returns to in-service tracking.

If no maintenance is required, the part continues in service until it reaches the end of its operational life, at which point it moves to part retirement. The NFT is updated one final time to record the retirement, effectively closing the digital record of the part’s lifecycle.

3.6. The Workflow for Flight Logs Using NTF-Based Technology

The workflow for flight logs using an NFT-based system presents a technologically advanced approach to recording, verifying, and utilizing flight data (Figure 8) to create a secure, transparent, and immutable record of each flight, from pre-flight preparations to post-flight analysis.

The process begins with the pre-flight stage, where a unique NFT is created for the upcoming flight. This digital token serves as the primary record for all subsequent flight-related data and activities.

Next, the flight initiation stage occurs. Here, the NFT is updated with initial flight details, including departure information, flight plan, and any pre-flight checks. Concurrently, crew records are accessed and integrated into the flight log, updating the NFT with information about the flight crew, their qualifications, and duty times.

As the flight progresses, the in-flight data collection phase begins. During this crucial stage, the NFT is continuously updated with real-time flight data. This may include navigation information, aircraft performance metrics, weather conditions, and any significant events or decisions made during the flight.

Upon landing, the post-flight stage commences. The NFT is updated with arrival information, any notable occurrences during the flight, and preliminary post-flight checks. This stage also involves updating crew records with completed flight hours and any relevant notes.

Following the post-flight updates, the data verification process begins. This stage is critical for ensuring the accuracy and integrity of the flight log. The NFT data is cross-checked against other systems and verified for compliance with regulatory requirements. Any discrepancies or issues are identified and addressed at this point.

Once verified, the process moves to log finalization. Here, the flight log NFT is sealed, creating a finalized, immutable record of the entire flight. This finalized log is then linked to the broader aircraft record, contributing to the comprehensive history of the aircraft’s operations.

The completed flight log NFT becomes a valuable resource for several subsequent processes:

• The flight log provides crucial data for planning and scheduling aircraft maintenance, ensuring that all required services are performed at the appropriate intervals.
• The detailed flight data captured in the NFT enables the in-depth analysis of aircraft and crew performance, helping to identify trends, efficiencies, and areas for improvement.
• In the event of any irregularities or incidents, the immutable and comprehensive nature of the NFT-based flight log provides investigators with reliable, tamper-proof data for analysis and incident investigation.

3.7. The Workflow for Ownership and Leasing Using NTF-Based Technology

The workflow for ownership and leasing using an NFT-based system presents an approach to managing aircraft ownership and leasing arrangements (Figure 9). This system provides a secure, transparent, and efficient method for tracking the lifecycle of aircraft ownership and leasing transactions.

The process begins with aircraft manufacture, where a unique NFT is created to represent the aircraft. This digital token serves as the immutable record of the aircraft’s existence and subsequent ownership history.

Initial ownership is established immediately after manufacture. The NFT is updated to reflect the first owner’s details, creating a verifiable record of the aircraft’s provenance. This stage is influenced by ongoing asset management practices and must comply with regulatory compliance requirements. Both of these elements provide regular updates and verifications to the NFT throughout the aircraft’s lifecycle.

From this point, the workflow diverges based on whether the aircraft will be transferred to a new owner or leased. This decision point is represented by the “Transfer or lease?” diamond in the flowchart.

If a transfer occurs, the process moves to ownership transfer. Here, the NFT is updated to reflect the change in ownership. This update includes details of the transaction, such as the date of transfer and the new owner’s information. Once the transfer is complete, the new owner is registered in the system, and the NFT is updated accordingly.

In the case of a lease, the process follows the lease agreement path. The NFT is updated with the terms of the lease, including the lessee’s details, lease duration, and any specific conditions. This creates a transparent and immutable record of the leasing arrangement.

Following the lease agreement, the aircraft enters lessee operations. During this phase, the NFT is regularly updated to reflect the aircraft’s usage, maintenance, and any significant events that occur while under the lessee’s control. This ensures a comprehensive record of the aircraft’s history during the lease period.

The leasing process includes a decision point for lease expiration. If the lease has not expired, the aircraft remains in lessee operations. However, upon lease expiration, the process moves to lease return. At this stage, the NFT is updated to reflect the end of the lease agreement and any final inspections or conditions related to the return of the aircraft. Finally, the aircraft is returned to the lessor, and this transition is also recorded in the NFT.

Throughout this entire process, three overarching elements play crucial roles:

• Ongoing asset management involves continuous monitoring and updating of the aircraft’s status, value, and condition. Regular updates are made to the NFT to reflect changes in these aspects.
• All stages of ownership and leasing must adhere to relevant aviation regulations. The system verifies compliance at each step, with the NFT updated to reflect adherence to regulatory requirements.
• The NFT is consistently updated throughout the aircraft’s lifecycle, ensuring that all relevant information is current and accurately reflected in the digital record.

3.8. The Workflow for Technical Documentation Using NTF-Based Technology

The workflow for technical documentation using an NFT-based system presents an approach to creating, reviewing, approving, and managing technical documents in the aviation industry (Figure 10) to ensure the authenticity, traceability, and secure management of critical technical documentation throughout its lifecycle.

The process begins with document creation, where a new technical document is initiated. At this stage, a unique NFT is created to represent the document. This digital token serves as the document’s immutable identifier and will store all subsequent changes and approvals throughout its lifecycle.

Following creation, the document enters the internal review phase. The NFT is updated to reflect that the document is under review, including details such as reviewers and review dates. Version control is applied throughout this process, managing different iterations of the document as it undergoes revisions.

After internal review, the workflow reaches an approval decision point. If not approved, the document goes through revisions, with each revision recorded in the NFT, maintaining a clear audit trail of changes. If approved, the document moves to the regulatory approval stage.

During regulatory approval, the NFT is updated to indicate that the document is undergoing external regulatory review. This stage is crucial for ensuring compliance with aviation industry standards and regulations.

The regulatory approval process leads to another decision point. If not approved, the document enters the address regulatory feedback stage, where necessary changes are made based on regulatory input. These changes are meticulously recorded in the NFT. If approved, the document proceeds to publication.

At the publication stage, the NFT is updated to reflect the document’s final approved status, version number, and publication date. This creates an official, verifiable record of the document’s release.

Post-publication, the document enters the distribution phase. The NFT is updated with information about how and to whom the document is distributed. This is closely tied to access control, which manages who can view or modify the document, with all access permissions and activities recorded in the NFT.

Compliance tracking runs parallel to these processes, monitoring and recording in the NFT how the document adheres to relevant regulations and standards throughout its lifecycle.

User access represents the stage where end-users interact with the published document. The NFT continues to play a crucial role here, recording access patterns and ensuring users are viewing the most up-to-date version of the document.

The workflow includes a decision point to determine if an update required. If an update is necessary, the process cycles back to the document creation or internal review stage, initiating a new version of the document. This update process is carefully managed through version control, ensuring that all changes are tracked, and previous versions are preserved.

If no update is required, the document remains in active use, with the NFT continuing to record its usage and status.

3.9. The Workflow for Quality Assurance Using NTF-Based Technology

The workflow for quality assurance using an NFT-based system presents an approach to ensuring and maintaining quality standards in the aviation industry, creating an immutable, transparent record of all quality-related processes and decisions (Figure 11).

The process begins with quality standard definition, where specific quality criteria are established. At this stage, an NFT is created to represent these standards, serving as a digital, tamper-proof record of the quality requirements.

Simultaneously, supplier quality management is initiated to monitor and ensure the quality of inputs from external sources. This process feeds into the overall quality assurance system, with its findings and actions recorded in the NFT.

The defined standards then move to process implementation, where they are put into practice. The NFT is updated to reflect how the standards are applied in real-world operations.

Following implementation, a quality check is performed to assess adherence to the defined standards. The results of this check are recorded by updating the NFT, ensuring a transparent record of quality assessments.

If the quality check reveals that standards are not met, the process loops back for further refinement and implementation. If standards are met, the process moves to quality approval, and the NFT is updated to reflect this positive outcome.

Parallel to these processes, an audit cycle is in place. Audit planning schedules regular internal audits, the results of which are recorded in the NFT. If an internal audit is passed, an external audit is conducted for independent verification. The outcomes of both internal and external audits are meticulously logged in the NFT.

After the external audit, there is a decision point regarding whether the certification is maintained. If maintained, the process moves to recertification, updating the NFT to reflect the renewed certification status. If it is not maintained, a certification suspension status is recorded in the NFT, and the process moves to address the audit findings to rectify the issues.

Customer feedback is also integrated into the quality assurance process. This feedback is analyzed and incorporated into the continuous monitoring phase, with relevant insights and actions recorded in the NFT.

The continuous monitoring phase is a critical component of the workflow. It involves the ongoing surveillance of processes, products, and services. The NFT is regularly updated with monitoring data, creating a real-time record of quality performance.

If issues are detected during continuous monitoring, an issue investigation is initiated, followed by root cause analysis. The findings from these stages are recorded in the NFT, providing a clear trail of problem identification and diagnosis.

Based on the root cause analysis, corrective actions are implemented. These actions and their outcomes are logged in the NFT, demonstrating the responsive nature of the quality assurance system.

3.10. Mathematical Framework for NFT-Based Lifecycle Management in Aviation

In this section, a unified model of framework is presented, illustrating how NFTs are applied across key workflows, including aircraft parts tracking, maintenance records, certification, supply chain management, flight logs, ownership, technical documentation, and quality assurance. The model demonstrates how NFTs are created and updated at various stages of the lifecycle, ensuring data integrity, compliance, and operational efficiency. Each NFT acts as a living digital entity that evolves over time, reflecting the current state and history of the asset it represents, thereby facilitating informed decision-making and improving safety, traceability, and accountability in the aviation industry.

The key concept is that every entity in the aircraft lifecycle, whether a physical part, a maintenance event, a flight, or documentation, is associated with a unique NFT, which serves as an immutable, traceable digital representation.

The main definitions are provided below:

• $P_i$ represents an aircraft part, $M_j$ represents a maintenance event, $F_k$ represents a flight log, and $D_l$ represents the technical documentation.
• $N_i, N_{M_j}, N_{F_k}, N_{D_l}$ represent the NFTs associated with each part, maintenance event, flight, and document, respectively.
• The operation $⨁$ represents the process of appending new information to an NFT, thus updating it.
• The subscripts $i,j,k,l$ are index variables representing distinct components, events, or instances within the lifecycle model. Specifically, these subscripts are used to identify individual parts, maintenance events, certification processes, and operational statuses, providing a method to differentiate between multiple entities within the same category.
• The subscripts $man, cert, repair$ represent specific stages or activities related to the component’s lifecycle, such as manufacturing ($man$), certification ($cert$), and repair processes ($repair$).

1. Part tracking

Each part $P_i$ is manufactured and assigned a unique NFT $N_i$:

$$N_i=f(P_i,D_{man},C_{cert})$$

where $D_{man}$ is the manufacturing data, and $C_{cert}$ is the certification information.

The NFT is updated throughout the part’s lifecycle:

$$N_i^{t+1}=N_i^t⨁(D_{inst},A_{craft},H_{flight},D_{op},M_i)$$

where $D_{inst}$ is the installation data, $A_{craft}$ is the aircraft it is installed on, $H_{flight}$ is the flight hours, $D_{op}$ is the operational data, and $M_i$ is any maintenance history.

2. Maintenance records

Each maintenance event $M_j$ is tracked by its own NFT $N_{M_j}$. This NFT is created when a maintenance event is scheduled:

$$N_{M_j}=f(M_j,D_{sched})$$

where $D_{sched}$ refers to the scheduled maintenance data. It includes information related to the planned maintenance event for an aircraft part or system. These data typically consist of the following: the scheduled date and time for the maintenance event, the location where the maintenance is to take place, the specific aircraft part or system requiring maintenance, the type of maintenance (e.g., routine check, repair, overhaul), any resources (tools, personnel) needed for the maintenance.

NFT $N_{M_j}$ is updated with pre- and post-maintenance inspections $I_{pre},I_{post}$ actions, quality checks $Q_{check}$ and signoffs $A_{signoff}$:

$$N_{M_j}^{t+1}=N_{M_j}^t⨁(I_{pre},A_{maint},I_{post},Q_{check},A_{signoff})$$

where $A_{maint}$ represents the core actions that are recorded in the NFT associated with a maintenance event. This includes all activities and procedures performed during a maintenance event for an aircraft part, system, or the aircraft itself. The data typically consist of details of the maintenance tasks performed (e.g., repairs, replacements, adjustments, inspections), parts or components involved in the maintenance process, tools, materials, and resources used during the maintenance, technicians or personnel responsible for performing the maintenance, the time and date when the maintenance was carried out, any observations or issues encountered during the maintenance, and the results of the maintenance (e.g., whether the part was restored to serviceable condition).

Linking this maintenance NFT to the part’s NFT:

$$N_i^{updated}=N_i⨁N_{M_j}$$

3. Certification and compliance

For certification, a unique $N_{C_n}$ is created for each certification process $C_n$. This NFT tracks the entire certification lifecycle:

$$N_{C_n}=f(C_n,A_{appl})$$

where $A_{appl}$ refers to the application for certification data. This represents the initial request or submission made for the certification of an aircraft part, system, or process. The data typically includes the details of the part or system seeking certification, information about the applicant (manufacturer, operator, or other entity), the specific certification requirements or standards being applied for, supporting documentation related to compliance, testing, and prior assessments, any regulatory references or guidelines that the certification must adhere to.

$N_{C_n}$ is updated with assessments, testing results, and final certification status:

$$N_{C_n}^{t+1}=N_{C_n}^t⨁(A_{test},T_{result},C_{certified})$$

where $A_{test}$ is the assessment, $T_{result}$ is the test result, and $C_{certified}$ is the certification issuance.

4. Supply chain management

The NFT $N_i$ for each part $P_i$ is created upon manufacturing and updated through the supply chain process:

$$N_i^{t+1}=N_i^t⨁(L_{warehouse},O_{order},S_{shiping},R_{receved})$$

where $L_{warehouse}$ is the warehouse location, $O_{order}$ is the order data, $S_{shiping}$ is the shipping information, and $R_{receved}$ confirms receipt of the part.

5. Flight logs

For each flight $F_k$, an NFT $N_{F_k}$ is created at the beginning of the flight:

$$N_{F_k}=f(F_k,D_{pre-flight})$$

where $D_{pre-flight}$ refers to the pre-flight data. These include all relevant information and checks performed before an aircraft’s flight. The data typically consist of flight plan details, such as the route, departure, and destination; aircraft status, including fuel levels, weight distribution; and any pre-flight inspections, crew assignments (including pilot and crew member information, qualifications, and duty hours); weather conditions and forecasts that may affect the flight; aircraft systems checks, covering engines, avionics, hydraulics, and other critical systems; regulatory compliance checks, ensuring that the aircraft and crew meet all legal and safety requirements before departure; any notable issues or observations during the pre-flight inspection.

$N_{F_k}$ is updated throughout the flight, recording in-flight data and post-flight details:

$$N_{F_k}^{t+1}=N_{F_k}^t⨁(D_{in-flight},D_{post-flight},C_{verified})$$

where $D_{in-flight}$ is in-flight data, $D_{post-flight}$ is post-flight data, and $C_{verified}$ is compliance verification.

6. Ownership and leasing

Each aircraft is assigned a unique NFT $N_A$ upon manufacture. Ownership or lease events update the NFT with ownership transfers $O_{transfer}$ or lease agreements $L_{lease}$:

$$N_A^{t+1}=N_A^t⨁(O_{transfer},L_{lease},R_{return})$$

where $R_{return}$ is the return of the aircraft at the end of a lease.

7. Technical documentation

For each technical document $D_l$, an NFT $N_{D_l}$ is created to represent the document. This NFT is updated as the document goes through review, approval, and revision stages:

$$N_{D_l}^{t+1}=N_{D_l}^t⨁(V_{review},A_{approval},R_{revision})$$

where $V_{review}$ represents versioning during review, $A_{approval}$ is approval data, and $R_{revision}$ contains the revision history.

8. Quality assurance

Each quality standard $Q_s$ is associated with an NFT $N_{Q_s}$. The NFT is updated as audits ($A_{audit})$, checks ${(Q}_{check}),$ and certifications ${(C}_{cert}$) occur:

$$N_{Q_s}^{t+1}=N_{Q_s}^t⨁(A_{audit},Q_{check},C_{cert})$$

The NFTs $N_i,N_{M_j},N_{F_k},N_{D_l},N_{C_n},N_A,N_{Q_s},$ representing different entities and events in the aviation lifecycle, interact with one another. For example, an aircraft part’s NFT $N_i$ is linked to its maintenance records $N_{M_j}$, certification records $N_{C_n}$, flight logs $N_{F_k}$, and quality assurance data $N_{Q_s}$:

$$N_i^{final}=N_i⨁(N_{M_j},N_{F_k},N_{C_n},N_{Q_s})$$

This ensures complete traceability and compliance throughout the part’s lifecycle.

The integrated model describes how NFTs are created and updated throughout the entire aviation lifecycle, capturing manufacturing, maintenance, certification, supply chain, flight operations, ownership, documentation, and quality assurance. These NFTs ensure that all relevant data are securely stored and accessible for auditing, compliance, and operational decisions.

4. Discussion

The discussion is structured to analyze the proposed framework from a theoretical standpoint, focusing on its potential impact, benefits, and challenges within the aviation industry. The methodology involves a systematic examination of each component of the framework—digital twins, NFTs, and blockchain integration—assessing their individual contributions, as well as their combined effect on lifecycle management. The analysis begins by exploring the theoretical advantages of adopting these technologies, followed by a critical evaluation of potential limitations, including technical, regulatory, and operational challenges. Comparisons with existing approaches are incorporated to contextualize the framework within current industry practices, highlighting both unique contributions and areas requiring further research. This structured approach aims to provide a comprehensive understanding of the framework’s implications and to guide future practical implementations.

4.1. Opportunities for NFT-Based Lifecycle Management of Aviation Components

The aviation industry, known for its stringent safety standards and complex supply chains, is constantly seeking innovative ways to enhance efficiency, traceability, and reliability. NFTs present a groundbreaking opportunity to improve the lifecycle management of aviation components. By using blockchain technology, NFTs can create unique, immutable digital representations of physical assets, offering unprecedented levels of transparency and data integrity throughout a component’s lifecycle (Figure 12).

1. Enhanced traceability and authenticity

One of the primary opportunities NFTs offer is enhanced traceability. As illustrated in the Figure 12, an NFT is created at the manufacturing stage and continuously updated throughout the component’s lifecycle. This digital fingerprint ensures that every step of the component’s journey—from certification and supply chain to installation and maintenance—is recorded in a tamper-proof manner. This level of traceability is crucial in combating counterfeit parts, a significant issue in the aviation industry that can compromise safety and reliability.

2. Streamlined certification process

The certification stage, as shown in the diagram, can be significantly streamlined through NFTs. Regulatory compliance and quality assurance documentation can be linked directly to the component’s NFT. This creates a single source of truth for all certification-related information, reducing paperwork and simplifying audits. Regulatory bodies can have real-time access to this information, potentially speeding up approval processes.

3. Efficient supply chain management

NFTs can revolutionize supply chain management in aviation. As the diagram indicates, the NFT is updated as the component moves through the supply chain. This real-time tracking can help in inventory management, reducing delays, and ensuring that the right parts are available when and where they are needed. It also aids in provenance tracking, which is crucial for maintaining the integrity of the supply chain.

4. Optimized installation and in-service management

During the installation and in-service phases, NFTs continue to play a crucial role. The diagram shows how an NFT is updated at each stage, capturing installation details and in-service performance data. This continuous data collection enables predictive maintenance strategies, potentially reducing downtime and extending the life of components.

5. Data-driven maintenance decisions

The maintenance decision point in the diagram highlights another key opportunity. By analyzing the rich historical data stored in the NFT, maintenance teams can make more informed decisions. This data-driven approach can optimize maintenance schedules, reduce unnecessary part replacements, and ultimately enhance safety and cost-efficiency.

6. Comprehensive digital twin integration

Perhaps the most transformative aspect illustrated in the diagram is the continuous update link between each stage and the digital twin. NFTs can serve as a bridge between the physical component and its digital representation. This integration allows for real-time monitoring, simulation, and analysis, enabling more accurate predictions of component behavior and performance optimization.

7. End-of-life management and circular economy

The retirement stage shown in the diagram opens up opportunities for better end-of-life management. NFTs can store the complete history of a component, including its materials and usage. This information can be invaluable for recycling or repurposing parts, contributing to a more sustainable and circular economy in aviation.

8. Enhanced regulatory compliance

Throughout the lifecycle, NFTs can simplify compliance with aviation regulations. The immutable record of a component’s history, from manufacturing to retirement, provides regulators with a transparent and easily auditable trail, potentially streamlining inspections and approvals.

The integration of NFTs in aviation-component lifecycle management offers numerous opportunities to enhance safety, efficiency, and sustainability in the aviation industry. By providing an immutable, comprehensive digital record of each component’s journey, NFTs have the potential to transform how the industry manages its critical assets.

4.2. Updating the Digital Twin Throughout an Aviation Component’s Lifecycle

The digital twin concept plays a pivotal role in the NFT-based lifecycle management system for aviation components. Figure 13 illustrates the ecosystem where the physical component is digitally mirrored through a digital twin NFT, which is continuously updated with data from various sources. This dynamic updating process ensures that the digital twin remains an accurate representation of the physical component throughout its lifecycle.

The lifecycle begins with the physical component, equipped with sensors. These sensors are the primary interface between the physical world and the digital realm, capturing real-time data about the component’s condition, performance, and environment.

The sensors transmit data to an IoT gateway, which acts as a bridge between the physical component and the digital systems. The data then flow to edge computing systems, where they are processed in real time. This initial processing at the edge reduces latency and allows for quick, localized decision-making.

The diagram shows various systems feeding data into a centralized cloud platform:

• Maintenance systems provide data on repairs, inspections, and component health.
• Supply chain systems contribute logistics data, tracking the component’s movement and history.
• Flight systems input operational data, offering insights into how the component performs during actual flights.
• Quality assurance systems add data related to quality checks and performance metrics.
• Regulatory systems provide compliance-related information, ensuring the component meets all necessary standards.
• Human input allows for manual updates, incorporating expert knowledge and observations.

The cloud platform serves as the central nervous system of the digital twin ecosystem. It aggregates, processes, and analyzes data from all these diverse sources, creating a comprehensive view of the component’s status and history.

The cloud platform continuously updates the digital twin NFT with the latest aggregated and processed data. This NFT becomes a living, breathing digital representation of the physical component, evolving in real time as new information becomes available.

The updated digital twin NFT feeds into predictive analytics systems. These systems use the rich, historical data stored in the NFT to forecast potential issues, optimize maintenance schedules, and predict the component’s future performance. The insights generated are then shared with relevant stakeholders, enabling data-driven decision-making throughout the component’s lifecycle.

The diagram shows an API connection from the digital twin NFT to external systems. This suggests that the digital twin can interact with and provide data to other systems outside the immediate ecosystem, enhancing interoperability and expanding its utility.

A crucial aspect of this system is the feedback loop. The predictive analytics insights can influence the decisions made in various stages of the lifecycle, from maintenance scheduling to flight operations. These decisions, in turn, generate new data that feed back into the system, creating a continuous improvement cycle.

As the component moves through different stages of its lifecycle, from manufacturing to installation, regular operation, maintenance, and eventually retirement, the digital twin is updated to reflect these transitions. Each stage brings new types of data and considerations, all of which are incorporated into the evolving digital twin.

Even as the component approaches the end of its operational life, the digital twin continues to be updated. This historical record becomes invaluable for analyzing the component’s full lifecycle performance, informing the design and management of future components, and potentially assisting in recycling or repurposing efforts.

4.3. The Relationship Between Updates and the NFT Structure

The relationship between updates and the NFT structure in the context of aviation-component lifecycle management is a sophisticated interplay among blockchain technology, smart contracts, and decentralized storage (Figure 14).

The process begins with “Update sources” providing new data about the aviation component. These sources could include IoT sensors, maintenance logs, flight data, or manual inputs from technicians. These new data trigger the update process.

The new data are fed into a smart contract, which is executed on the blockchain. This smart contract is crucial, as it contains the logic to process updates, ensuring that only valid and authorized changes are made to the component’s digital representation.

After processing the update, the smart contract determines the “Update type”. This classification is a critical step in maintaining the integrity and efficiency of the NFT structure. Figure 14 shows two primary types of updates:

• Minor updates are frequent, small changes that do not significantly alter the component’s status. Examples might include routine sensor readings or minor maintenance checks.
• Major updates are substantial changes that materially affect the component’s status or history. Examples could include major repairs, certification renewals, or significant performance alterations.

For major updates, the process involves updating the NFT metadata. This is a crucial step in the NFT structure, as it allows for significant changes to be recorded directly on the blockchain. The NFT metadata contains essential information about the component, such as its status, ownership history, and critical events in its lifecycle.

Minor updates are handled differently. Instead of altering the NFT metadata, these updates are recorded in the InterPlanetary file system (IPFS) or other decentralized storage systems. IPFS is a distributed and decentralized file storage and sharing system. It is designed to create a more efficient and resilient method of storing and accessing files, websites, applications, and data [67]. This approach allows for efficient handling of frequent, smaller updates without constantly modifying the blockchain-based NFT.

The NFT metadata contain a pointer to the latest version of the component data stored in the IPFS. When a major update occurs, this pointer is updated to reflect the new state of the component. For minor updates, a new hash is generated in the IPFS, representing the updated state of the component data.

The IPFS/decentralized storage plays a crucial role in this structure. It stores the detailed component data, which includes all the historical information and current state of the aviation component. This approach allows for storing large amounts of data off-chain while maintaining a secure, immutable reference on the blockchain via the NFT.

The blockchain records all major updates and the latest pointers to the IPFS data. This creates an immutable, tamper-proof record of significant events in the component’s lifecycle.

This dual structure of blockchain-based NFT and IPFS storage ensures both the integrity of critical data (through blockchain immutability) and the accessibility and updateability of detailed component information (through IPFS).

4.4. The Relationships Between NTF-Based Components in the Aviation Lifecycle Management System

The relationships between data sources, digital twins, blockchain, NFTs, and other components in this aviation lifecycle management system create a complex, interconnected ecosystem (Figure 15).

The system begins with the physical aviation component and various data sources. These data sources feed information about the component’s status, performance, and environment directly into the digital twin. This relationship establishes the foundation for creating an accurate digital representation of the physical asset.

The digital twin serves as a crucial bridge between the physical world and the digital realm. It is represented by an NFT and stored in decentralized storage. This relationship allows for a comprehensive, up-to-date digital model of the physical component, which can be accessed and analyzed without direct interaction with the physical asset.

The NFT acts as the unique digital identity for the aviation component. It is hosted on the blockchain, which provides immutability and security. The NFT points to the detailed data stored in the decentralized storage, creating a link between the blockchain’s security and the rich data set of the digital twin.

The blockchain hosts the NFTs and serves as the underlying trust layer for the entire system. It ensures the integrity and immutability of critical data, particularly the NFT metadata and ownership information.

Smart contracts play a central role in managing the interactions within the system. They are triggered by stakeholders and interact with the NFTs. This relationship allows for the automated, trustless execution of predefined rules and processes, such as ownership transfers or regulatory checks.

The stakeholders interact with the system primarily through smart contracts. They can trigger actions, access information, and manage the NFTs. This relationship ensures that all stakeholder interactions are recorded and executed according to predefined rules.

Regulatory systems verify compliance using the NFTs. This relationship allows for real-time, transparent regulatory oversight without the need for manual audits or inspections.

The supply chain tracks components using the NFTs. This relationship enables seamless tracking of parts throughout their lifecycle, from manufacture to retirement, enhancing traceability and reducing the risk of counterfeit parts entering the system.

Decentralized storage serves as the repository for the detailed digital twin data. Both the NFT and the digital twin point to this storage, creating a relationship that balances the need for detailed data storage with blockchain efficiency.

The system incorporates a continuous update cycle. Data sources feed new information to the digital twin, which is then stored in the decentralized storage. The NFT is updated to point to the latest version of these data, ensuring that the digital representation always reflects the current state of the physical component.

The intricate relationships between data sources, digital twins, blockchain, NFTs, and other components in this system create a robust, transparent, and efficient framework for managing aviation components throughout their lifecycle. This ecosystem uses the strengths of each technology—the immutability of blockchain, the uniqueness of NFTs, the detail of digital twins, and the capacity of decentralized storage—to address the complex needs of the aviation industry.

4.5. Benefits of NFT-Based Approach for Aviation Component Lifecycle Management

The proposed NFT-based approach to aviation-component lifecycle management offers several key benefits that address critical challenges in the aviation industry:

• Each component is represented by a unique NFT, creating an immutable digital fingerprint that tracks the component’s entire lifecycle. This significantly reduces the risk of counterfeit parts entering the system.
• Real-time tracking of components through their NFTs enhances inventory management, reduces delays, and ensures timely availability of parts.
• The system simplifies the certification process by linking all relevant information directly to the component’s NFT. This creates a single source of truth, reducing paperwork and simplifying audits.
• Rich historical data stored in NFTs enables informed decision-making for maintenance. Integration with digital twin technology allows for real-time monitoring and performance optimization.
• Comprehensive tracking of component history and performance data contributes to improved risk assessment and proactive maintenance.
• The hybrid approach of blockchain and decentralized storage balances security needs with system efficiency for managing vast amounts of data.
• The system facilitates better information sharing among various stakeholders in the aviation industry, fostering a more connected ecosystem.
• Optimized maintenance schedules, reduced paperwork, and improved supply chain efficiency can lead to significant cost savings.
• Complete historical records stored in NFTs can facilitate more effective recycling or repurposing of parts at the end of their lifecycle.
• The system’s design allows for the integration of future technologies, ensuring long-term value and relevance.

This NFT-based approach offers a comprehensive solution to many challenges faced by the aviation industry, potentially improving safety, efficiency, and sustainability in aviation operations.

4.6. Challenges of NFT-Based Approach for Aviation Component Lifecycle Management

While the NFT-based approach for aviation-component lifecycle management offers significant benefits, it also faces several key challenges:

• Integrating blockchain, NFTs, digital twins, and decentralized storage creates a complex ecosystem that requires significant expertise to develop, maintain, and upgrade.
• Efficiently storing, managing, and ensuring the quality of vast amounts of data generated throughout component lifecycles poses a significant challenge.
• While blockchain enhances security, protecting the system from cyber attacks and balancing transparency with privacy protection remain crucial concerns.
• Obtaining approval from aviation authorities for blockchain and NFT technologies in critical systems and ensuring compatibility with international regulatory frameworks present significant hurdles.
• Overcoming resistance to change, integrating with legacy systems, and providing comprehensive training across the industry are key challenges for widespread adoption.
• Maintaining fast transaction speeds and network capacity as the system grows to encompass more components and stakeholders is a critical technical challenge.
• Significant investment is required for the initial setup, ongoing operations, and transitioning from existing systems to the new NFT-based approach.
• Seamless operation across different blockchain platforms and integration with various external systems require careful standardization efforts.
• Clarifying the legal status of NFTs as representations of physical components and determining liability in cases of system failures need to be addressed.
• Addressing the potential high energy consumption of blockchain networks, especially in the context of the aviation industry’s sustainability goals, is an important consideration.

Despite these challenges, the potential benefits of this innovative system make it a promising avenue for improving safety, efficiency, and transparency in the aviation industry.

4.7. Future Directions of Research for NFT-Based Aviation Component Lifecycle Management

The NFT-based approach for aviation-component lifecycle management opens several promising avenues for future research:

• Blockchain optimization with improved scalability, energy efficiency, and transaction speed.
• AI and machine learning integration with NFT-based systems to enhance predictive maintenance and optimize supply chain management.
• Interoperability and standardization for NFT metadata, smart contract protocols, and data formats specific to aviation components.
• Smart components directly linked to their digital NFT twins for real-time data updates.
• Enhanced security and privacy, tailored for aviation industry requirements.
• Legal and regulatory frameworks to accommodate blockchain and NFT technologies, including the legal status of NFTs as digital representations of physical assets.
• Expanded NFT applications for other aspects of aviation operations.
• Examination of how permanent, immutable records of component lifecycles might impact aircraft resale values, insurance practices, and future design processes.

These research directions aim to address current limitations, enhance system capabilities, and explore new applications of NFT-based technologies in aviation.

5. Conclusions

This paper presents a comprehensive framework for implementing NFT-based decentralized algorithms for digital twin management in aviation, focusing on component lifecycle tracking. The proposed system uses blockchain technology, smart contracts, and decentralized storage to create a robust, transparent, and efficient ecosystem for managing aviation components throughout their lifecycle.

The integration of NFTs with digital twins offers new opportunities for enhancing traceability, authenticity, and data integrity in the aviation industry. By creating unique digital representations of physical components, this approach addresses critical challenges in supply chain management, maintenance, certification, and regulatory compliance. The system’s ability to provide real-time, immutable records of a component’s entire history—from manufacture to retirement—has the potential to significantly improve safety, reduce fraud, and optimize operational efficiency.

The key benefits of this NFT-based approach include enhanced traceability and authenticity verification, streamlined certification processes, efficient supply chain management, and data-driven maintenance decisions. The system also facilitates comprehensive digital twin integration, enabling real-time monitoring, simulation, and performance optimization of aviation components.

However, the implementation of such a system is not without challenges. Addressing these challenges will be crucial for the successful implementation and widespread adoption of NFT-based systems in aviation.

Future research directions should focus on blockchain optimization for improved scalability, integration of AI and machine learning for enhanced predictive capabilities, development of interoperability standards, and exploration of smart components directly linked to their digital NFT twins.

The NFT-based approach to aviation-component lifecycle management represents a significant advancement in how the industry can manage its critical assets.