Virtualization Approaches for the Design, Characterization, and Control of Food Industry Plants

This thesis investigates the potential of digital technologies in advancing and optimizing the food industry. Through a series of case studies, the research explores how tools such as Computational Fluid Dynamics (CFD), Digital Twins, virtual sensors, machine vision, and simulation-based inventory management can address critical challenges in food processing and handling. Conducted in close collaboration with industry partners, these projects were designed to address real-world needs while also contributing valuable insights to academic research. Each application showcased the flexibility and effectiveness of digital techniques in enhancing plant performance, improving product quality, and promoting sustainability. Key findings include the role of CFD and numerical simulations in deeply characterizing both innovative and traditional processes, facilitating optimization, and filling gaps in scientific literature. The thesis also examines applications beyond standard CFD use, proposing simulation-based virtual sensors as a novel solution for monitoring and controlling food industry plants. These virtual sensors, developed through parametric simulation campaigns, provide insights in areas where physical sensors are unavailable or impractical. Further analyses focused on implementing CFD models within Digital Twin frameworks. Experimentally validated models were applied to two pilot plants installed at the University of Parma. After enabling real-time communication between physical and digital counterparts, the Digital Twins will be deployed to assess their effectiveness in dynamically adjusting the operating point to maintain quality standards and adapt to system conditions that evolve over time. The integration of Machine vision, traditionally used mainly for quality control, into these Digital Twin systems, was proposed, with the aim of creating highly integrated adaptive environments aimed at zero-defect manufacturing. Additionally, the thesis introduced a modeling approach for inventory management of perishable goods, presenting and evaluating practical solutions for reducing food waste. Future research aims to link simulation outcomes with consumer behavior insights gathered from the presented survey, to enhance both sustainability and profitability in food industry inventory systems. This thesis makes a significant contribution to the pursuit of digitalisation in the food industry. As the demand for food products grows, and quality standards rise, the importance of digital technologies will only continue to increase. This work provides practical insights to address current industry challenges, and sets a foundation for future innovations that balance efficiency, sustainability, and continuous improvement in the food sector.