Extraction of sugar from sugar beets is a process optimized over decades based on experience gathered during production. This process improvement is achieved without any systematic approach for optimization which raised the question whether such a mature process can be further optimized effectively, applying methods developed in the last decade like statistical experiment design or physicochemical modeling. Viable areas of operation for the respective approaches will be assessed and discussed using the example of sucrose extraction from sugar beet. Operating conditions are optimized regarding extraction kinetics and equilibrium behavior. Physicochemical modeling, however, requires detailed information on phase equilibria, fluid dynamics, and mass transfer effects. Here, the phase ratio can be identified as a sensitive parameter and process performance like the HETP (high equivalent of a theoretical plate) value can be enhanced. Therefore, the volumetric productivity serves as indicator. Potentials of process design and process optimization by a combination of statistical design of experiments and physicochemical modeling approaches are assessed, and respective possibilities and limitations are discussed.

For years, microtechnology is being considered as an emerging technique for chemical engineering tasks to overcome safety issues corresponding to high volumes and gaining higher selectivities and yields in reaction technology. Whereas in reaction technology a broad variety of microstructured equipment is available, in product purification/separation adequate equipment is missing. Research is focused on modular fast and flexible smaller production plants being operated continuously instead of batchwise in order to reduce engineering efforts and time‐to‐process. To cope with these demands, an appropriate definition of modules, which could be easily chosen and combined, is inevitable. In addition, these modules have to be well characterized concerning fluid dynamics and separation performance. This paper focuses on the characterization of available modules/devices. A standard method and analysis of the results concerning manufacturing accuracy and operation range is proposed. Miniplant technology is described as an efficient tool to validate process concepts proposed by process simulation studies. Necessary model parameters are determined for industrial complex mixtures in miniaturized laboratory equipment. Parameters are calculated model based to gain maximal accuracy. State of the art of miniplant technology is described and basic characteristic data are presented.

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