Analytische Chemie
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The future competitiveness of the process industry and their providers depends on its ability to deliver high quality and high value products at competitive prices in a sus-tainable fashion, and to adapt quickly to changing customer needs. The transition of process industry due to the mounting digitalization of technical devices and their pro-vided data used in chemical plants proceeds. Though, the detailed characteristics and consequences for the whole chemical and pharmaceutical industry are still unfore-seeable, new potentials arise as well as questions regarding the implementation. As the digitalization gains pace fundamental subjects like the standardization of device interfaces or organization of automation systems must be answered. Still, process in-dustry lack of sufficient system and development concepts with commercial advantage from this trend.
Compared to traditional batch processes, intensified continuous production allows new and difficult to produce compounds with better product uniformity and reduced consumption of raw materials and energy. Flexible (modular) chemical plants can pro-duce various products using the same equipment with short down-times between campaigns, and quick introduction of new products to the market.
Full automation is a prerequisite to realize such benefits of intensified continuous plants. In continuous flow processes, continuous, automated measurements and closed-loop control of the product quality are required. Consequently, the demand for smart sensors, which can monitor key variables like component concentrations in real-time, is increasing. Low-Field NMR spectroscopy presents itself as such an upcoming smart sensor1,2 (as addressed, e.g., in the CONSENS project3).
Systems utilizing such an online NMR analyzer benefits through short development and set-up times when applied to modular production plants starting from a desired chemical reaction3. As an example for such a modular process unit, we present the design and validation of an integrated NMR micro mixer based on computational mod-elling suited for a desired chemical reaction. This method includes a proper design of a continuous reactor, which is optimized through computational fluid dynamics (CFD) for the demands of the NMR sensor as well as for the given reaction conditions. The system was validated with a chemical reaction process.
References:
[1] M. V. Gomez et al., Beilstein J. Org. Chem. 2017, 13, 285-300
[2] K. Meyer et al., Trends Anal. Chem. 2016, 83, 39-52
[3] S. Kern et al., Anal Bioanal Chem. 2018, 410, 3349-3360
Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short down-times between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds. Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts while being based on “chemical” information.
As an example, a fully automated NMR sensor is introduced, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. Therefore, a commercially available benchtop NMR spectrometer was adapted to the full requirements of an automated chemical production environment such as, e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. NMR appeared as preeminent online analytical tool and allowed using a modular data analysis tool, which even served as reliable reference method for further PAT applications.
A full integration and intelligent interconnection of such systems and processes progresses only hesitantly. The talk should encourage to re-think digitization of process industry based on smart sensors, actuators, and communication more comprehensively and informs about current technical perspectives such as the “one-network paradigm”, edge computing, or virtual machines. These give smart sensors, actuators, and communication a new perspective.