Automation of Batch Vacuum Pan Control Based on the Modeled Boiling Curve of Massecuite

Introduction: The process of boiling massecuite in batch vacuum pans (BVPs) is a key stage in sugar production, determining its quality and energy efficiency. Despite a significant amount of research, the relationship between the pan fill level (L) and the dynamics of the dry solids content (Bx) remains insufficiently studied, which limits the possibilities for precise process control.

Purpose: To establish a quantitative relationship between the fill level of a BVP, the Bx dynamics, and the parameters of the boiling curve for the development of an optimized control strategy for the massecuite boiling process.

Materials and Methods: Experimental methods of online monitoring (Bx, level, temperature, pressure) on UVA-60S type pans were used, along with mathematical modeling of the boiling curve based on a sigmoid function and an adaptive MPC algorithm. Statistical data processing included correlation and regression analysis.

Results: It was found that the optimal pan fill level (60–70 %) ensures maximum process efficiency. The implementation of the MPC algorithm significantly improved crystal quality (reduction in the size variation coefficient) and reduced energy consumption. A strong correlation was revealed between the supersaturation gradient and crystal quality (r = 0.82).

Conclusion: The research results contribute to the international agenda on energy efficiency management and the development of intelligent control systems in the food industry. The proposed method demonstrates potential for integration with digital twins, ensuring precise control and adaptation to changing production conditions. The practical significance of the work is confirmed by successful testing in industrial conditions, making it applicable for optimizing processes at sugar plants. A promising direction is the further development of hybrid control systems using artificial intelligence methods.

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