Enhancing Manufacturing Agility: The Role of Digital Twins and AI in Reconfigurable Production Systems

This paper highlights the development and implementation of a digital twin for a pilot within the AGILEHAND project, aimed at improving planning and resource management in food processing. By integrating realtime data, the digital twin enhances forecast accuracy, optimizes raw material usage, and ensures efficient scheduling. The system models the physical production line, including multiple processing stations and conveyors, using an open source discrete-event simulation. Additionally, key elements such as products and operators are modelled to reflect real-world interactions, allowing for detailed analysis of production line behaviour across various scenarios. Moreover, Artificial intelligence plays a critical role in optimizing operations, managing order processing, and addressing inventory overlap to ensure smooth transitions between production phases. This comprehensive approach facilitates precise production tracking and adaptive scheduling, ultimately improving operational efficiency and resource utilization.