TY - JOUR A1 - Eifert, T. A1 - Eisen, K. A1 - Maiwald, Michael A1 - Herwig, C. T1 - Current and future requirements to industrial analytical infrastructure—part 2: smart sensors N2 - Complex processes meet and need Industry 4.0 capabilities. Shorter product cycles, flexible production needs, and direct assessment of product quality attributes and raw material attributes call for an increased need of new process analytical technologies (PAT) concepts. While individual PAT tools may be available since decades, we need holistic concepts to fulfill above industrial needs. 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). Part 2 of this feature article series describes the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality. The smart sensor consists of (i) chemical and process information in the physical twin by smart field devices, by measuring multiple components, and is fully connected in the IIoT 4.0 environment. In addition, (ii) it includes process intelligence in the digital twin, as to being able to generate knowledge from multi-sensor and multi-dimensional data. The cyber-physical system (CPS) combines both elements mentioned above and allows the smart sensor to be self-calibrating and self-optimizing. It maintains its operation autonomously. Furthermore, it allows—as central PAT enabler—a flexible but also target-oriented predictive control strategy and efficient process development and can compensate variations of the process and raw material attributes. Future cyber-physical production systems—like smart sensors—consist of the fusion of two main pillars, the physical and the digital twins. We discuss the individual elements of both pillars, such as connectivity, and chemical analytics on the one hand as well as hybrid models and knowledge workflows on the other. Finally, we discuss its integration needs in a CPS in order to allow is versatile deployment in efficient process development and advanced optimum predictive process control. KW - Smart sensors KW - Industry 4.0 KW - Digital twins KW - Process intelligence KW - Process analytical technology KW - Physical twin KW - Cyber-physical system PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-503980 DO - https://doi.org/10.1007/s00216-020-02421-1 SN - 1618-2642 VL - 412 IS - 9 SP - 2037 EP - 2045 PB - Springer CY - Berlin Heidelberg AN - OPUS4-50398 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Integrated and networked systems and processes – A perspective for digital transformation of our chemical and pharmaceutical production N2 - Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. The potential of digital technologies belongs to these. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. At the same time, we need to move towards knowledge-based production that takes into account all essential equipment, process and control data from plants and laboratories and makes valuable expertise available and transferable. The potential of data from production together with its contextual information is often not yet consistently used today for a comprehensive understanding of production. By giving examples this paper outlines a possible more holistic approach to digitalisation and the use of machine-based methods in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes. T2 - GDCh Science Forum 2021 - GDCh Wissenschaftsforum 2021 CY - Online meeting DA - 29.08.2021 KW - Process analytical technology KW - Online NMR spectroscopy KW - Process industry KW - Industry 4.0 KW - Digital transformation KW - Autonomous chemistry PY - 2021 AN - OPUS4-53171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -