AI control for pasteurized soft-boiled eggs

Podržaj, Primož (avtor), Kozjek, Dominik (avtor), Škulj, Gašper (avtor), Požrl, Tomaž (avtor), Jenko, Marjan (avtor)

This paper presents a novel approach to thermal process control in the food industry, specifically targeting the pasteurization and cooking of soft-boiled eggs. The unique challenge of this process lies in the precise temperature control required, as pasteurization and cooking must occur within a narrow temperature range. Traditional control methods, such as fuzzy logic controllers, have proven insufficient due to their limitations in handling varying loads and environmental conditions. To address these challenges, we propose the integration of robust reinforcement learning (RL) techniques, particularly the utilization of the Deep Q-Network (DQN) algorithm. Our approach involves training an RL agent in a simulated environment to manage the thermal process with high accuracy. The RL-based system adapts to different heat capacities, initial conditions, and environmental variations, demonstrating superior performance over traditional methods. Experimental results indicate that the RL-based controller significantly improves temperature regulation accuracy, ensuring consistent pasteurization and cooking quality. This study opens new avenues for the application of artificial intelligence in industrial food processing, highlighting the potential for RL algorithms to enhance process control and efficiency.

• Jezik: Angleški jezik
• Ključne besede: AI temperature control, artificial intelligence, machine learning, pasteurized soft-boiled eggs, robust reinforcement learning
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FS - Fakulteta za strojništvo
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2025
• Št. strani: Str. 1-26
• Številčenje: Vol. 14, iss. 18, 3171
• PID: 20.500.12556/RUL-173355
• UDK: 641:004.896
• ISSN pri članku: 2304-8158
• DOI: 10.3390/foods14183171
• COBISS.SI-ID: 249147395
• Datum objave v RUL: 16.09.2025

Gradivo je del revije

• Naslov: Foods
• Skrajšan naslov: Foods
• Založnik: MDPI
• ISSN: 2304-8158
• COBISS.SI-ID: 512252472

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Projekti

• Financer: ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
• Številka projekta: P2-0270
• Naslov: Proizvodni sistemi, laserske tehnologije in spajanje materialov