# NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking
## 4 Discussion
### 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.  
Figure 13: Updating the digital twin.  
* 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.