The manufacturing process of frozen dairy desserts, such as ice cream and gelato, is very sensitive to human errors in ingredient preparation: even minor variations in the ingredient mix can lead to quality issues and material waste. To become more sustainable, next generation ice cream making machines need to implement intelligent and adaptive processes that are both efficient and forgiving of human mistakes in mixture preparations. Toward that goal, we developed Hard-O-Tronic AI-driven (HOT-AI), a novel edge AI solution specifically designed for Carpigiani’s ice cream making machines. Leveraging the innovative multimilestone classification methodology, HOT-AI performs inference at multiple stages—or milestones—during the ice cream making process, with increasing accuracy over time. This enables HOT-AI to take corrective actions by adapting the preparation process accordingly, thus improving batch-to-batch uniformity, minimizing ingredient waste, and enhancing production efficiency, cost-effectiveness, and sustainability. HOT-AI has been successfully validated under real production conditions, and its large-scale implementation is planned across Carpigiani Group machines.

Smart and Sustainable Ice Cream Making Through Edge Machine Learning

Tabanelli, Filippo;Dahdal, Simon
;
Belletti, Nicolas;Bellodi, Elena;Ngatcha, Franck;Lazzarini, Roberto;Stefanelli, Cesare;Tortonesi, Mauro
2026

Abstract

The manufacturing process of frozen dairy desserts, such as ice cream and gelato, is very sensitive to human errors in ingredient preparation: even minor variations in the ingredient mix can lead to quality issues and material waste. To become more sustainable, next generation ice cream making machines need to implement intelligent and adaptive processes that are both efficient and forgiving of human mistakes in mixture preparations. Toward that goal, we developed Hard-O-Tronic AI-driven (HOT-AI), a novel edge AI solution specifically designed for Carpigiani’s ice cream making machines. Leveraging the innovative multimilestone classification methodology, HOT-AI performs inference at multiple stages—or milestones—during the ice cream making process, with increasing accuracy over time. This enables HOT-AI to take corrective actions by adapting the preparation process accordingly, thus improving batch-to-batch uniformity, minimizing ingredient waste, and enhancing production efficiency, cost-effectiveness, and sustainability. HOT-AI has been successfully validated under real production conditions, and its large-scale implementation is planned across Carpigiani Group machines.
2026
Tabanelli, Filippo; Dahdal, Simon; Belletti, Nicolas; Bellodi, Elena; Ngatcha, Franck; Lazzarini, Roberto; Stefanelli, Cesare; Tortonesi, Mauro...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2616832
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