TY - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Bornemann-Pfeiffer, Martin A1 - Paul, Andrea A1 - Meyer, Klas A1 - Kern, Simon T1 - Already producing or still calibrating? – Online NMR spectroscopy as smart field device N2 - The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. The talk introduces a smart online NMR sensor module provided in an explosion proof housing as example. This sensor was developed for an intensified industrial process (pharmaceutical lithiation reaction step) funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. Industry 4.0, IIoT, or Lab 4.0 will enable us to handle more complex processes in shorter time. Intensified production concepts require for adaptive analytical instruments and control technology to realize short set-up times, modular control strategies. They are based on a digitized Laboratory 4.0. T2 - GA-Conference CY - BASF, Ludwigshafen, Germany DA - 16.05.2018 KW - Process Monitoring KW - Online NMR Spectroscopy KW - Industrie 4.0 KW - Indirect Hard Modeling KW - Laboratory 4.0 KW - CONSENS PY - 2018 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-44895 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Eisen, K A1 - Eifert, T A1 - Herwig, C A1 - Maiwald, Michael T1 - Current and future requirements to industrial analytical infrastructure—part 1: process analytical laboratories JF - Analytical and Bioanalytical Chemistry N2 - The competitiveness of the chemical and pharmaceutical industry is based on ensuring the required product quality while making optimum use of plants, raw materials, and energy. In this context, effective process control using reliable chemical process analytics secures global competitiveness. The setup of those control strategies often originate in process development but need to be transferable along the whole product life cycle. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (part 1) and smart sensors (part 2). In laboratories and pilot plants, offline chemical analytical methods are frequently used, where inline methods are also used in production. Here, a transferability from process development to the process in operation would be desirable. This can be obtained by establishing PAT methods for production already during process development or scale-up. However, the current PAT (Bakeev 2005, Org Process Res 19:3–62; Simon et al. 2015, Org Process Res Dev 19:3–62) must become more flexible and smarter. This can be achieved by introducing digitalization-based knowledge management, so that knowledge from product development enables and accelerates the integration of PAT. Conversely, knowledge from the production process will also contribute to product and process development. This contribution describes the future role of the laboratory and develops requirements therefrom. In part 2, we examine the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality—also within process development or scale-up facilities (Eifert et al. 2020, Anal Bioanal Chem). KW - Smart test laboratories KW - Laboratory 4.0 KW - Sustainable Production KW - Industry 4.0 PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-504020 DO - https://doi.org/10.1007/s00216-020-02420-2 SN - 1618-2642 VL - 412 IS - 9 SP - 2027 EP - 2035 PB - Springer CY - Berlin Heidelberg AN - OPUS4-50402 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -