Modeling of the blockchain-empowered Cloud 4D Printing Services Collaboration Digital Twin platform oriented on supply–demand

Recently, the widespread adoption of digital twin and blockchain technologies within the frameworks of Industry 4.0 and intelligent manufacturing has intensified the emphasis on globalization and social collaborative manufacturing. This study aims to address the fragmentation of global information and enhance the collaborative utilization and optimal sharing of underutilized manufacturing resources and capabilities through the development of the C4DPSC_DT platform. To meet these demands, our research focuses on the domain of 4D printing and introduces the blockchain-empowered C4DPSC_DT platform, which is based on dynamic supply and demand principles. This platform is meticulously analyzed to unveil its complex nature, characterized by the integration of physical entities, virtual twin representations, and collaborative services, forming five distinct attributes under this triadic fusion. To further enhance the adaptability of the C4DPSC_DT platform, we propose an adaptive collaborative microservice architecture. Additionally, to emphasize the collaborative service attributes of the platform, we introduce the blockchain-empowered C4DPSC framework. This framework incorporates a collaborative multi-chain blockchain structure and the HotStuff consensus algorithm, facilitating the creation of a secure, distributed, traceable, and transparent environment for sharing C4DP resources and collaboration in C4DP services, thereby establishing decentralized and trustworthy collaborative service connections. Moreover, we systematically decompose the collaborative process into five stages, providing a comprehensive lifecycle solution for the systematic analysis and understanding of the 4D Printing Service collaboration process. Finally, through detailed case studies, we empirically validate the exceptional performance of the C4DPSC_DT platform, confirming its superior functionality and robustness.

Text 124023.pdf - Published Version Restricted to Repository staff only Download (4MB) Official URL or Download Paper: https://link.springer.com/article/10.1007/s00500-0...

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