Focus on SMEs experiments: AI at the Edge for Zero Defect Food Industry and Sustainability Gain

WHAT ABOUT THE EXPERIMENT? 

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As part of the AI REDGIO 5.0 project, Quescrem and Gradiant are leading an experiment that applies AI and digital twin technologies to transform cream cheese production. The goal is to improve product quality and reduce waste by creating a smart, responsive production process that learns and adapts in real time. 

The experiment combines process data from storage and production lines such as temperature, pressure, and ingredient characteristics with sustainability indicators like energy and water consumption. By developing predictive models, the system can forecast product quality outcomes during production and recommend optimal settings to ensure consistency and efficiency. 

Following a successful first phase in a simulated environment, the next step is to deploy the solution directly at Quescrem’s plant. A key focus of this phase is making the system more intuitive for human operators, through user-friendly interfaces and real-time feedback. This human-centric approach ensures that technology supports workers on the factory floor, rather than replacing them. 

 

WHAT IS EXPECTED? 

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The experiment aims to create a self-adaptive production process that leverages AI-driven predictions and prescriptions to continuously optimize efficiency, quality, and sustainability. By integrating human-machine interaction, the system empowers plant operators to supervise, validate, and improve AI performance in real time. 

For Quescrem, the end-user, the benefits include reduced waste, improved product consistency, and a more sustainable production process. For Gradiant, the technology provider, the experiment highlights the practical application of advanced AI and edge computing in SME manufacturing environments. Together, they are driving innovation within the agri-food sector and contributing to the broader goals of AI REDGIO 5.0.