TY - RPRT A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Maiwald, Michael ED - Maiwald, Michael T1 - Validation report on NMR 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. Smart sensors enable concepts like self-diagnostics, self-calibration, and self-configuration/ parameterization whenever our current automation landscape allows it. Here we summarize the currently discussed general requirements for process sensors 4.0 and introduce a smart online NMR sensor module as example, which was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (www.consensspire.eu). KW - Process Monitoring KW - Online NMR Spectroscopy KW - Indirect Hard Modeling KW - Process Control KW - Process Analytical Technology KW - CONSENS PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-435521 SP - 1 EP - 31 AN - OPUS4-43552 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Zientek, Nicolai A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon T1 - Strangers in the Night—Smart Process Sensors in Our Current Automation Landscape 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. Smart sensors enable concepts like self-diagnostics, self-calibration, and self-configuration/parameterization whenever our current automation landscape allows it. Here we summarize the currently discussed general requirements for process sensors 4.0 and introduce a smart online NMR sensor module as example, which was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). T2 - Eurosensors 2017 Conference CY - Paris, France DA - 03.09.2017 KW - Process Monitoring KW - Smart Sensors KW - CONSENS KW - Online NMR Spectroscopy KW - Mini-plant PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-415772 UR - http://www.mdpi.com/2504-3900/1/4/628 VL - 1 SP - 628 EP - 631 PB - MDPI CY - Basel AN - OPUS4-41577 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Guhl, Svetlana A1 - Kern, Simon A1 - Meyer, Klas A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Maiwald, Michael T1 - Online NMR Spectroscopy for Process Monitoring in Intensified Continuous Production Plants N2 - Process analytical techniques are extremely useful tools for chemical production and manufacture and are of particular interest to the pharmaceutical, food and (petro-) chemical industries. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analysers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack. A major advantage of NMR spectroscopy is that the method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method which is independent of the matrix. This is an important prerequisite for robust data evaluation strategies within a control concept and reduces the need for extensive maintenance of the evaluation model over the time of operation. Additionally, NMR spectroscopy provides orthogonal, but complimentary physical information to conventional, e.g., optical spectroscopy. It increases the accessible information for technical processes, where aromatic-toaliphatic conversions or isomerizations occur and conventional methods fail due to only minor changes in functional groups. As a technically relevant example, the catalytic hydrogenation of 2-butyne-1,4-diol and further pharmaceutical reactions were studied using an online NMR sensor based on a commercially available low-field NMR spectrometer within the framework of the EU project CONSENS (Integrated Control and Sensing). T2 - 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017) CY - Potsdam, Germany DA - 10.05.2017 KW - Process Monitoring KW - CONSENS KW - Online NMR Spectroscopy KW - Process Analytical Technology KW - Process control KW - Hydration KW - EuroPACT PY - 2017 SP - 103 EP - 103 CY - Frankfurt a. M. AN - OPUS4-40231 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Wander, Lukas A1 - Paul, Andrea A1 - Bremser, Wolfram A1 - Maiwald, Michael T1 - Mathematical and statistical tools for online NMR spectroscopy in chemical processes N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environ¬ments for advanced process monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS. We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes. T2 - Advanced Mathematical and Computational Tools in Metrology and Testing conference CY - Glasgow, United Kingdom DA - 29.08.2017 KW - Online NMR Spectroscopy KW - Process Control KW - Partial Least Squares Regression KW - Indirect Hard Modelling KW - Quantum Mechanics KW - First Principles PY - 2018 SN - 978-9-813-27429-7 VL - 89 SP - 229 EP - 234 PB - World Scientific CY - New Jersey AN - OPUS4-51391 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Wander, Lukas A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gottu Mukkula, A. R. A1 - Holtkamp, M. A1 - Salge, M. A1 - Fleischer, C. A1 - Weber, N. A1 - King, R. A1 - Engell, S. A1 - Paul, Andrea A1 - Pereira Remelhe, M. A1 - Maiwald, Michael T1 - Flexible Automation with compact NMR instruments N2 - Modular plants using intensified continuous processes represent an appealing concept to produce pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes, and 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 includes a compact Nuclear Magnetic Resonance (NMR) spectrometer for online quality monitoring as well as a new model-based control approach. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including ro-bust evaluation of sensor data. Here, we present alternatives for the quantitative determination of the analytes using modular, physically motivated models. These models can be adapted to new substances solely by the use of their corresponding pure component spectra, which can either be derived from experimental spectra as well as from quantum mechanical models or NMR predictors. Modular means that spec-tral models can simply be exchanged together with alternate reagents and products. Beyond that, we comprehensively calibrated an NIR spectrometer based on online NMR process data for the first time within an industrial plant. The integrated solution was developed for a metal organic reac-tion running on a commercial-scale modular pilot plant and it was tested under industrial conditions. T2 - 7th Annual PANIC Conference CY - Hilton Head Island, South Carolina, USA DA - 03.03.2019 KW - Online NMR Spectroscopy PY - 2019 AN - OPUS4-47715 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Gottu Mukkula, A. R. A1 - Kern, Simon A1 - Salge, M. A1 - Holtkamp, M. A1 - Guhl, Svetlana A1 - Fleischer, C. A1 - Meyer, Klas A1 - Remelhe, M. A1 - Maiwald, Michael A1 - Engell, S. T1 - An Application of Modifier Adaptation with Quadratic Approximation on a Pilot Scale Plant in Industrial Environment N2 - The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties. KW - Process Analytical Technology KW - Online NMR Spectroscopy KW - Process Industry KW - Iterative real-time optimization KW - Modifier adaptation KW - Plant-model mismatch KW - Reactor control KW - CONSENS PY - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-524531 SN - 1522-2640 VL - 53 IS - 2 SP - 11773 EP - 11779 PB - Elsevier CY - Amsterdam AN - OPUS4-52453 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -