The best method for process control is the use of model‐based solutions, based on process analytical technology for online monitoring of critical process variables, product quality attributes, or a holistic process state estimation. Mechanistic models as well as data‐driven techniques are essential for real‐time process monitoring. Their main characteristics, advantages and disadvantages, and the link between both are discussed as well as the synergetic effects, benefits, and drawbacks resulting from their combination. Aspects and differences of the computational model life cycle management are highlighted.

Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance. Graphical abstract Electronic supplementary material The online version of this article (10.1007/s00216-019-01752-y) contains supplementary material, which is available to authorized users.

Abstract. This case study compares the usefulness and applicability of eight computer tools with respect to the validation of logic control programs for continuous processes. Six simulation packages (Taylor's Matlab-based simulator, Simulink/StateFlow, gPROMS, Shift, Dymola, and BaSiP) and two verification tools (SMV and HyTech) were applied to a single process control example with non-trivial continuous dynamics. The paper presents a detailed description of this benchmark example. Short introductions to the tools are given and the application results are decribed and discussed with emphasis on the suitability to the problem and the numerical performance.

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