Utilizing digital twins and hybrid modeling to achieve efficient supply chain in hybrid production systems

In today’s rapidly changing manufacturing environment, efficient supply chain management is a key factor in enhancing a company’s competitiveness. Traditional supply chain management methods face problems such as data silos and slow response times, and urgently need to introduce technological means. The rise of digital twins and hybrid modeling technology provides new ideas for solving these problems. This study focuses on analyzing the application of digital twin technology in hybrid production by establishing a framework that combines digital twin and hybrid models, including creating digital twin spaces, reconstructing old models, and algorithm testing. In the subsequent system design, a collaborative supply chain model based on digital twins was constructed, and data collection for manufacturing execution modules, development of fault feature diagnosis algorithms, and supply chain data assurance strategies were implemented. The research results indicate that the combination of digital twin technology and hybrid modeling can effectively improve the collaborative efficiency and fault response capability of the supply chain. After implementation, the response time of the system has been significantly shortened compared to traditional methods, and the overall operating costs have been significantly reduced. This verifies the feasibility of using digital twins and hybrid modeling to achieve efficient supply chains in hybrid production systems, providing effective management tools for manufacturing enterprises and promoting the development of intelligent supply chains.