# NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking
## 1 Introduction
### 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.