AI control for pasteurized soft-boiled eggs

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

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.

• Language: English
• Keywords: AI temperature control, artificial intelligence, machine learning, pasteurized soft-boiled eggs, robust reinforcement learning
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FS - Faculty of Mechanical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2025
• Number of pages: Str. 1-26
• Numbering: Vol. 14, iss. 18, 3171
• PID: 20.500.12556/RUL-173355
• UDC: 641:004.896
• ISSN on article: 2304-8158
• DOI: 10.3390/foods14183171
• COBISS.SI-ID: 249147395
• Publication date in RUL: 16.09.2025

Record is a part of a journal

• Title: Foods
• Shortened title: Foods
• Publisher: MDPI
• ISSN: 2304-8158
• COBISS.SI-ID: 512252472

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Projects

• Funder: ARIS - Slovenian Research and Innovation Agency
• Project number: P2-0270
• Name: Proizvodni sistemi, laserske tehnologije in spajanje materialov