DOI: 10.3390/foods15213827 ISSN: 2304-8158

Ball Mill Refining in Confectionery Manufacturing: Processing Parameters, Fat Structure, Emulsification, and Rheological Properties—A Review

Marko Petković, Biljana Lončar, Nemanja Miletić

Ball mill refiners (BMRs) are widely used in confectionary manufacturing, particularly for producing chocolate, compound coatings, and nut-based pastes by integrating size reduction, dispersion, and partial conching into a single compact unit. This review critically examines the effects of key operational parameters—such as agitator shaft speed (ASS), refining time (RT), grinding media mass (GM) and thermal control—and their cascading effects on energy consumption (EC), particle size distribution (PSD), rheological properties, and final product quality. Recent literature was synthesized to examine how specific mechanical variables interact with different fat systems, including cocoa butter and alternative fats, and emulsifiers such as lecithin and polyglycerol polyricinoleate (PGPR), thereby influencing crystallization behavior, texture, and sensory quality. The reviewed findings indicate that greater refining intensity does not necessarily result in improved product quality, since excessive particle size reduction increases the specific surface area and may increase viscosity and fat requirements. The effects of processing parameters are strongly formulation-dependent, particularly in systems containing alternative fats and different emulsifier combinations. These relationships demonstrate that optimizing BMR operation requires balancing particle size reduction, energy consumption, rheological properties, and the desired quality attributes rather than maximizing refining intensity. Based on the reviewed literature, an integrated approach linking processing conditions, formulation characteristics, and product quality is proposed as a practical framework for BMR process control. Future research should focus on standardized reporting of operating conditions, in-line monitoring, and the development of predictive models that account for interactions between processing parameters and formulation characteristics.

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