In a dynamic and uncertain global environment, supply chain reconfiguration has emerged as a solution for managing disruptions and enhancing operational resilience. This paper presents an intelligent reconfiguration framework developed following an in-depth analysis of the existing literature on reconfiguration, the application of knowledge graph and the integration of Artificial Intelligence in supply chain reconfiguration. This comprehensive literature review highlights gaps in current methodologies, particularly in achieving efficient reconfiguration. In response, we propose a novel framework that leverages real-world data, Digital Twin modeling, Dynamic Knowledge Graph and Artificial Intelligence-driven Decision Making to enable intelligent supply chain reconfiguration. This framework facilitates the continuous evaluation and optimization of supply chain configurations, while incorporating key performance indicators such as sustainability. By using the Artificial Intelligence to enhance predictive capabilities and decision-making, the framework ensures that supply chains can seamlessly adapt to disruptions and evolving requirements. This work is driven by the need for sustainable and resilient supply chain that maintain a competitive edge in dynamic environments, a goal that can be achieved through efficient dynamic reconfiguration.