Integrated Cloud-Twin Synchronization for Supply Chain 5.0

The digital twin is thus emerging means of improving real-world performance from virtual spaces, especially relatedto Supply Chain 5.0 in Industry 5.0. This framework employs the integration of cloud computing and digital twin technologies to secure data storage, trusted tracking, and high reliability, is architectural for the integration of supply-chain sustainable enterprises. In this work, we introduce a high level architecture of cloud-based digital twin model for supply chain 5.0 , which was created to align the system of supply chain through real-time observation as well as real-timesupply chain 5.0 decision-making and control. This study introduces a cloud-based twin optimization model for Supply Chain 5.0, validated through genetic algorithm (GA) simulations. The model determines optimal weights to balance objectives, achieving an optimal objective function value that reflects trade-offs among operational efficiency, cost, and sustainability. A convergence plot illustrates the model’s iterative solution improvements, demonstrating its dynamic adaptability. Lastly, the proposed model defines and test a supply chain performance analysis through dynamic simulations.