AI Control for Pasteurized Soft-Boiled Eggs.

ABSTRACT: 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 s

SUBMITTER: Podrzaj P 

PROVIDER: S-EPMC12468857 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature