The automation of grading, handling and packaging of soft and deformable food products in the industry necessitates precision in manipulation, adaptive gripping, and real-time monitoring to ensure uniform quality and prevent damage. These aspects are the objectives of the European project AGILEHAND. This project aims at developing advanced technologies as a strategic instrument to improve flexibility, agility and reconfigurability of production and logistic systems of the manufacturing companies. In this context, this paper discusses the development of a data-driven framework for automated generation of simulation models for the realization of the digital twins in food factories. The core of this framework involves discrete event simulation: by real system data it is possible to streamline the reconfiguration of production and logistic systems. During this process, it is also possible to promptly identify design or process sequence problems at an early stage through cross-domain simulation. Firstly, this framework supports the project manager in scheduling production by optimising resources and minimising the order of Estimated Time of Arrival. Then, during the system monitoring phase, it simulates new scenario to find the proper corrective action when a significant deviation from the plan occurs. In the end, the accurate capture of dynamics arising in the physical layer allows an effective evaluation of their negative effects on the system’s overall operational state. This approach supports informed decision-making in planning and controlling logistics, production, and associated activities, providing a comprehensive framework for enhanced operational efficiency.