Blockchain-enabled digital twin integration for supply chain transparency enhancement in large-scale engineering project optimization - Liu, Yuejun; Nifa, Faizatul Akmar Abdul; Teong, Lim Kong (Edelweiss Applied Science and Technology, 2025)
In large-scale engineering projects, managing complex supply chains effectively is essential to ensure timely delivery, cost efficiency, and quality assurance. Traditional methods often fail to address key challenges in transparency, traceability, and security, leading to inefficiencies and vulnerabilities. To overcome these limitations, this research proposes the Blockchain-Integrated Digital Twin MBA Optimization Framework (BDT-MBA), which combines advanced blockchain security, digital twins (DT), and optimization techniques to improve supply chain management. Blockchain technology provides a decentralized and immutable system for secure data sharing, ensuring data integrity, transparency, and trust among stakeholders. Real-time updates are enabled through IoT sensors, which synchronize DTs with the physical state of assets, facilitating cyber-physical systems security. The DT framework delivers real-time insights into asset performance, forming the basis for optimized decision-making. The MBA analyzes data to optimize logistics, resource allocation, and system efficiency, aligning with the needs of internet services for adaptive and scalable supply chain operations. This framework mitigates cybersecurity threats, ensures privacy, and enhances the efficiency of sanitization (98.4%) and restoration (98.8%). The proposed BDT-MBA framework represents a robust and transformative approach for secure and transparent supply chain optimization in complex engineering projects. Integrating blockchain, IoT, and DTs demonstrates significant advancements in traceability, secure data management, and real-time decision-making for modern supply chain systems.