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A fuzzy logic control system is designed and applied to a proofing system. The controller is experimentally evaluated and the performance is compared to the ones from a PID controller. Dough pieces with different amounts of yeast added in the ingredients and in different temperature starting states are prepared and proofed with the supervision of the fuzzy control system. The controller is designed to maintain the volume of the dough pieces similar to volume expansion of a dough piece in standard conditions during the proofing process. Controllers are evaluated by means of performance criteria and the final volume of the dough samples. It is demonstrated that the fuzzy logic controller can provide significant better control, does not require a mathematical model and has better disturbance rejection properties. [ABSTRACT FROM AUTHOR]

Abstract: Despite the importance of the proofing process in baking industry, no online measurement system is available so far, which can supervise this process step. This article presents the application of a model‐based tuned PID controller to the proofing process in bread baking. The work includes developing an on‐line monitoring system in order to measure volume evaluation of dough pieces during the proofing process and applying the corrective actions to minimize the size variation caused by alteration in amount of yeast added to the ingredients. The controller was tuned by an optimization method. For this purpose, a mathematical model representing the volume evaluation of dough pieces during proofing was identified, which allows an off‐line search for optimal parameters of the controller. The application of the proposed control strategy to an actual proofing chamber for controlling dough leavening during the proofing process was found to be successful. Practical applications: Besides judging the right amount of proofing time, which is always challenging in the baking industry, alteration in ingredients and different starting states of the dough (normal dough frozen dough or thawed dough) will influence the required time for the proofing process. Any changes in time requirements in the process steps creates a backlog in the whole process, which will lead to inefficient manufacturing and low product quality. Online monitoring and automation process control of the proofing process is an alternative method to overcome these problems. The present research introduces an automated control system based on machine vision for controlling the proofing process in the baking industry. The automated control system is able to reduce the need for close monitoring and process adjustments by human operators, which leads to enhanced productivity and constant high product quality. [ABSTRACT FROM AUTHOR]

Dough fermentation is an important step during the preparation of fermented baking goods. For the supervision of dough fermentation, a continuous-discrete extended Kalman filter was applied, which uses an image analysis system as the measurement. By estimation a fixed number of gas bubbles inside the dough, the radius of an average bubble was determined. A mathematical dough model was used by the extended Kalman filter to estimate the radius of the average bubble, the CO2 concentration of the non-gas dough phase and the number of CO2 molecules in the average bubble. During a fermentation of 50 min, the extended Kalman filter estimated that the average radius increased from 50 µm to 127 µm, the CO2 concentration in the non-gas dough increased to 23 mol/m³, and the CO2 amount in the bubble increased from 0.1 × 10−10 to 4 × 10−10 mol. Also, the specific CO2 production rate was estimated to be in the range from 1.5 × 10−3 to more than 4 × 10−3 mol·m³/kg/s. The advantages of an extended Kalman filter for the supervision of the dough fermentation process are discussed. [ABSTRACT FROM AUTHOR]