# NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking
## 3 Results
### 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 \(\bigoplus\) 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:  
\[N_{i}^{t+1}=N_{i}^{t}\bigoplus\left(D_{inst},A_{craft},H_{flight},D_{op},M_{i}\right)\]  
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:  
\[N_{M_{j}}=f\left(M_{j},D_{sched}\right)\]  
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 \(A_{signoff}\):  
\[N_{M_{j}}^{t+1}=N_{M_{j}}^{t}\bigoplus\left(I_{pre},A_{maint},I_{post},Q_{ check},A_{signoff}\right)\]  
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.