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 UR - https://nbn-resolving.org/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 - JOUR A1 - Maiwald, Michael T1 - Voll integrierte und vernetzte Systeme und Prozesse - Perspektive: Smarte Sensorik, Aktorik und Kommunikation T1 - Fully integrated distributed systems and processes – Perspective: Smart sensors, actuators, and communication N2 - Unternehmen der chemischen Industrie müssen neuen Pfade beschreiten, um in einem veränderten Umfeld erfolgreich bestehen zu können. Dazu gehört insbesondere, das Potenzial digitaler Technologien zu nutzen. Die volle Integration und intelligente Vernetzung von Systemen und Prozessen kommt allerdings nur zögerlich voran. Dieser Beitrag ist ein Loblied auf die Feldebene. Er möchte dazu ermutigen, die Digitalisierung der Prozessindustrie auf Basis smarter Sensorik, Aktorik und Kommunikation ganzheitlicher zu denken und informiert über aktuelle technische Perspektiven, wie das Ein-Netzwerk-Paradigma, Ad-hoc-Vernetzungen, Edge-Computing, FPGAs, virtuelle Maschinen oder Blockchain. Diese geben smarter Sensorik, Aktorik und Kommunikation eine völlig neue Perspektive. N2 - Chemical companies must find new paths to success in a changing environment. In particular, this will involve exploiting the potential of digital technologies. However, the full integration and intelligent interconnection of systems and processes is only making slow progress. This contribution aims to encourage the more comprehensive use of digitization in the process industry based on smart sensors, actuators, and communications, and informs about current technical possibilities such as the “one-network paradigm”, ad-hoc connections, edge computing, FPGAs, virtual machines and blockchain. These offer a new scope for smart sensors, actuators, and communications. KW - Smarte Sensoren KW - Smarte Aktoren KW - Digitalisierung der Prozessindustrie KW - Prouess-Sensoren 4.0 KW - Smart sensors KW - Smart actuators KW - Digitization of process industry KW - Process sensors 4.0 PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-466642 DO - https://doi.org/10.17560/atp.v60i10.2376 SN - 2364-3137 VL - 60 IS - 10 SP - 70 EP - 85 PB - Vulkan Verlag CY - Essen AN - OPUS4-46664 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Kern, Simon A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Wander, Lukas A1 - Paul, Andrea 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. Here we introduce our smart online NMR sensor module provided in an explosion proof housing 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). 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. T2 - Tackling the Future of Plant Operation - Jointly towards a Digital Process Industry CY - Barcelona, Spain DA - 13.12.2017 KW - Process Monitoring KW - Smart Sensors KW - Online NMR Spectroscopy KW - Indirect Hard Modeling KW - Process Analytical Technology KW - CONSENS PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-434330 AN - OPUS4-43433 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon T1 - Sustainable and Flexible Production of High Quality Chemicals and Pharmaceuticals Using Smart Sensors and Modular Production Units 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. The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control and gives also an overview on direct dissolution studies of API cocrystals. T2 - Chemistry Group Seminar Pfizer Inc. CY - La Jolla, California, USA DA - 09.03.2018 KW - Process Monitoring KW - Online NMR Spectroscopy KW - Smart Sensors KW - Indirect Hard Modeling KW - Modular Production KW - CONSENS PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-444382 AN - OPUS4-44438 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Quantitative NMR Spectroscopy Uncertainty Analysis Workshop N2 - qNMR provides the most universally applicable form of direct concentration or purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. The workshop presents basic terms of statistics and uncertainty analysis, which are the basis for qNMR spectroscopy and data analysis such as, e.g., standard deviations, linear regression, significance tests, etc. and gives typical examples of applications in qNMR spectroscopy. T2 - Practical Applications of NMR in Industry Conference ​(PANIC) Validation Workshop 2018 CY - La Jolla, California, USA DA - 08.03.2018 KW - qNMR KW - NMR Validation KW - Basic Statistics KW - Linear Regression PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-444395 AN - OPUS4-44439 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Wander, Lukas A1 - Meyer, Klas A1 - Paul, Andrea T1 - Already Producing or Still Calibrating? – Advances of Model-Based Data Evaluation Concepts for Quantitative Online NMR Spectroscopy 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. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example. 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. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu). T2 - Practical Applications of NMR in Industry Conference (PANIC) 2018 CY - La Jolla, California, USA DA - 04.03.2018 KW - Process Monitoring KW - Process Control KW - Process analytical technology KW - Spectral Modeling KW - Smart Sensors KW - CONSENS KW - Industrie 4.0 PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-444357 AN - OPUS4-44435 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bröcker, S. A1 - Klaer, R.-H. A1 - Kockmann, N. A1 - Maiwald, Michael T1 - Process Industry United in the Digital World - The current landscape of research for the digitalization of the process industry N2 - The Tutzing Symposium "100 % digital: survival strategies for the process industry" (see 4.1) in April 2018 was characterized by a great momentum which has been taken up and continued until today. The aim was to implement the ideas from the Tutzing Symposium in a coordinated and targeted manner. For this purpose, development needs as well as the numerous currently planned or already started research and development activities in the context of digitalisation were first compiled and analysed. This resulted in the current research landscape for digitalization in the process industry. It now enables to identify open topics and to translate them into research funding programs as well as to define new projects in the dialogue between users, suppliers and research, which are to be meaningfully interlinked and consolidated with existing projects. Due to the strong interest in digitalisation, activities are constantly being added, so that this paper can only provide a snapshot of the situation in the period 2019-2020. KW - Process Industry KW - Digitalisation KW - Tutzing Symposion KW - research landscape KW - Process Control PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-512265 UR - https://processnet.org/en/TAKdigital.html SP - 1 EP - 15 AN - OPUS4-51226 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Martins, Inês C.B. A1 - Al-Sabbagh, Dominik A1 - Meyer, Klas A1 - Maiwald, Michael A1 - Scholz, G. A1 - Emmerling, Franziska T1 - Insight into the Structure and Properties of Novel Imidazole-Based Salts of Salicylic Acid N2 - The preparation of new active pharmaceutical ingredient (API) multicomponent Crystal forms, especially co-crystals and salts, is being considered as a reliable strategy to improve API solubility and bioavailability. In this study, three novel imidazole-based salts of the poorly water-soluble salicylic acid (SA) are reported exhibiting a remarkable improvement in solubility and dissolution rate properties. All structures were solved by powder X-ray diffraction. Multiple complementary techniques were used to solve co-crystal/salt ambiguities: density functional Theory calculations, Raman and 1H/13C solid-state NMR spectroscopies. In all molecular salts, the Crystal packing interactions are based on a common charged assisted +N-H SA)...O-(co-former) hydrogen bond interaction. The presence of an extra methyl group in different positions of the co-former, induced different supramolecular arrangements, yielding salts with different physicochemical properties. All salts present much higher solubility and dissolution rate than pure SA. The most promising results were obtained for the salts with imidazole and 1-methylimidazole co-formers. KW - Salicylic acid KW - Imidazole KW - Salts KW - Powder X-ray diffraction KW - SsNMR KW - DFT PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-502825 DO - https://doi.org/10.3390/molecules24224144 VL - 24 IS - 22 SP - 4144 PB - MDPI AN - OPUS4-50282 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kern, Simon A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Müller, S. A1 - Maiwald, Michael A1 - Kowarik, Stefan T1 - Artificial neural networks for quantitative online NMR spectroscopy N2 - Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data. KW - Online NMR spectroscopy KW - Real-time process monitoring KW - Artificial neural networks KW - Automation KW - Process industry PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-507508 DO - https://doi.org/10.1007/s00216-020-02687-5 SN - 1618-2642 VL - 412 IS - 18 SP - 4447 EP - 4459 PB - Springer CY - Berlin AN - OPUS4-50750 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR 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 - Engell, S. A1 - Paul, Andrea A1 - Pereira Remelhe, M. A1 - Maiwald, Michael T1 - Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals N2 - 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. KW - NMR Spectroscopy KW - NIR Spectroscopy KW - Real-time process monitoring KW - Real-time quality control KW - Continuous processes KW - CONSENS KW - Data Fusion PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-480623 DO - https://doi.org/10.1007/s00216-019-01752-y SN - 1618-2642 SN - 1618-2650 VL - 411 IS - 14 SP - 3037 EP - 3046 PB - Springer Nature CY - Heidelberg AN - OPUS4-48062 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 - 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 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 - TY - JOUR A1 - Maiwald, Michael T1 - Integrated and Networked Systems and Processes—A Perspective for Digital Transformation in Thermal Process Engineering N2 - Separation technology as a sub-discipline of thermal process engineering is one of the most critical steps in the production of chemicals, essential for the quality of intermediate and end products. The discipline comprises the construction of facilities that convert raw materials into value-added products along the value chain. Conversions typically take place in repeated reaction and separation steps—either in batch or continuous processes. The end products are the result of several production and separation steps that are not only sequentially linked, but also include the treatment of unused raw materials, by-products and wastes. Production processes in the process industry are particularly susceptible to fluctuations in raw materials and other influences affecting product quality. This is a challenge, despite increasing fluctuations, to deliver targeted quality and simultaneously meet the increasing dynamics of the market, at least for high value fine chemicals. In order to survive successfully in a changed environment, chemical companies must tread new paths. This includes the potential of digital technologies. The full integration and intelligent networking of systems and processes is progressing hesitantly. This contribution aims to encourage a more holistic approach to the digitalization in thermal process engineering by introduction of integrated and networked systems and processes. KW - Smarter Sensor KW - Digitalisation KW - Digital transformation KW - Process Industry KW - Thermal Process Engineering KW - Digital Twins PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-504964 DO - https://doi.org/10.3390/chemengineering4010015 SN - 2305-7084 VL - 4 IS - 15 SP - 1 EP - 9 PB - MDPI CY - Basel AN - OPUS4-50496 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Balderas-Xicohtencatl, R. A1 - Villajos Collado, José Antonio A1 - Casabán, J. A1 - Wong, D. A1 - Maiwald, Michael A1 - Hirscher, M. T1 - ZIF‑8 Pellets as a Robust Material for Hydrogen Cryo-Adsorption Tanks N2 - Cryoadsorption on the inner surface of porous materials is a promising solution for safe, fast, and reversible hydrogen storage. Within the class of highly porous metal−organic frameworks, zeolitic imidazolate frameworks (ZIFs) show high thermal, chemical, and mechanical stability. In this study, we selected ZIF-8 synthesized mechanochemically by twin-screw extrusion as powder and pellets. The hydrogen storage capacity at 77 K and up to 100 bar has been analyzed in two laboratories applying three different measurement setups showing a high reproducibility. Pelletizing ZIF-8 increases the packing density close to the corresponding value for a single crystal without loss of porosity, resulting in an improved volumetric hydrogen storage capacity close to the upper limit for a single crystal. The high volumetric uptake combined with a low and constant heat of adsorption provides ca. 31 g of usable hydrogen per liter of pellet assuming a temperature−pressure swing adsorption process between 77 K − 100 bar and 117 K − 5 bar. Cycling experiments do not indicate any degradation in storage capacity. The excellent stability during preparation, handling, and operation of ZIF-8 pellets demonstrates its potential as a robust adsorbent material for technical application in pilot- and full-scale adsorption vessel prototypes. KW - Hydrogen adsorption storage KW - Metal−organic frameworks KW - ZIF-8 KW - Cryoadsorption KW - Hydrogen Storage KW - MefHySto PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-569473 DO - https://doi.org/10.1021/acsaem.2c03719 SN - 2574-0962 SP - 1 EP - 8 PB - ACS Publications CY - Washington DC AN - OPUS4-56947 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bornemann-Pfeiffer, Martin A1 - Kern, Simon A1 - Maiwald, Michael A1 - Meyer, Klas T1 - Calibration-Free Chemical Process and Quality Control Units as Enablers for Modular Production N2 - Modular chemical production is a tangible translation of the digital transformation of the process industry for specialty chemicals. In particular, it enables the speeding-up of process development and thus a quicker time to market by flexibly connecting and orchestrating standardised physical modules and bringing them to life (i.e., parameterising them) with digitally accumulated process knowledge. We focus on the specific challenges of chemical process and quality control, which in its current form is not well suited for modular production and provide possible approaches and examples of the change towards direct analytical methods, analytical model transfer or machine-supported processes. KW - Modular Production KW - Chemical Process Control KW - Process Analytical Technology KW - Digital Transformation KW - Industry 4.0 PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-517264 DO - https://doi.org/10.1002/cite.202000150 SN - 1522-2640 VL - 93 IS - 1-2 SP - 62 EP - 70 PB - Wiley-VCH CY - Weinheim AN - OPUS4-51726 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Maiwald, Michael T1 - Metrologie für fortschrittliche Wasserstoffspeicherlösungen – Das EU-Projekt MefHySto T1 - Metrology for advanced hydrogen storage solutions – The EU project MefHySto N2 - Das europäische Projekt MefHySto befasst sich mit dem Bedarf an großmaßstäblichen Energiespeichern, die für eine Umstellung der Energieversorgung auf erneuerbare Energien erforderlich sind. Eine solche Speicherung ist entscheidend, um Energie zu Spitzenzeiten zu liefern, wenn die erneuerbaren Energiequellen schwanken. Eine mögliche Lösung für die Energiespeicherung ist der großtechnische Einsatz von Wasserstoff. Die messtechnische Rückführbarkeit in der Energieinfrastruktur für die Wasserstoffspeicherung ist dann von entscheidender Bedeutung und eine bessere Kenntnis der chemischen und physikalischen Eigenschaften von Wasserstoff sowie rückführbare Messungen und validierte Techniken unverzichtbar. N2 - The European project MefHySto addresses the need of large-scale energy storage, which is required for a shift to renewable energy supply. Such storage is mandatory to supply energy at peak times when renewable sources fluctuate. A possible solution for energy storage is large-scale use of hydrogen. Metrological traceability in the energy infrastructure for hydrogen storage is then crucial and a better knowledge of the chemical and physical properties of hydrogen as well as traceable measurements and validated techniques are indispensable. KW - Wasserstoff KW - Wasserstoffspeicher KW - Infrastruktur KW - Metrologie KW - PEM-Wasserelektrolyse KW - Rückverstromung KW - Lastwechsel KW - Wasserstoff-Qualität PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-556451 UR - https://gwf-gas.de/forschung-entwicklung/metrologie-fuer-fortschrittliche-wasserstoffspeicherloesungen-das-eu-projekt-mefhysto/ SN - 2366-9594 VL - 163 IS - 9 SP - 38 EP - 45 PB - Vulkan Verlag CY - Essen AN - OPUS4-55645 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bornemann-Pfeiffer, Martin A1 - Meyer, Klas A1 - Lademann, J. A1 - Kraume, M. A1 - Maiwald, Michael T1 - Contributions towards variable temperature shielding for compact NMR instruments N2 - The application of compact NMR instruments to hot flowing samples or exothermically reacting mixtures is limited by the temperature sensitivity of permanent magnets. Typically, such temperature effects directly influence the achievable magnetic field homogeneity and hence measurement quality. The internal-temperature control loop of the magnet and instruments is not designed for such temperature compensation. Passive insulation is restricted by the small dimensions within the magnet borehole. Here, we present a design approach for active heat shielding with the aim of variable temperature control of NMR samples for benchtop NMR instruments using a compressed airstream which is variable in flow and temperature. Based on the system identification and surface temperature measurements through thermography, a model predictive control was set up to minimise any disturbance effect on the permanent magnet from the probe or sample temperature. This methodology will facilitate the application of variable-temperature shielding and, therefore, extend the application of compact NMR instruments to flowing sample temperatures that differ from the magnet temperature. KW - Benchtop NMR KW - Continuous Processes KW - Inline Analytics KW - Model Predictive Control KW - Process Analytical Tecnology KW - Temperature Control PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-579219 DO - https://doi.org/10.1002/mrc.5379 SN - 1097-458X SP - 1 EP - 10 PB - John Wiley & Sons Ltd. AN - OPUS4-57921 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 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-524531 DO - https://doi.org/10.1016/j.ifacol.2020.12.685 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 - TY - CONF A1 - Meyer, Klas A1 - Paul, Andrea A1 - Ruiken, J.-P. A1 - Westad, Frank A1 - Illner, M. A1 - Müller, D. A1 - Esche, E. A1 - Repke, J.-U. A1 - Maiwald, Michael T1 - Online Spectroscopy in Microemulsions – A Process Analytical Approach for a Hydroformylation Mini-plant N2 - Within the Collaborative Research Center InPROMPT a novel process concept for the hydroformylation of long-chained olefins is studied in a mini-plant, using a rhodium complex as catalyst in the presence of syngas. Recently, the hydroformylation in micro¬emulsions, which allows for the efficient recycling of the expensive rhodium catalyst, was found to be feasible. However, the high sensitivity of this multi-phase system with regard to changes in temperature and composition demands a continuous observation of the reaction to achieve a reliable and economic plant operation. For that purpose, we tested the potential of both online NMR and Raman spectroscopy for process control. The lab-scale experiments were supported by off-line GC-analysis as a reference method. A fiber optic coupled probe of a process Raman spectrometer was directly integrated into the reactor. 25 mixtures with varying concentrations of olefin (1-dodecene), product (n-tridecanal), water, n-dodecane, and technical surfactant (Marlipal 24/70) were prepared according to a D-optimal design. Online NMR spectroscopy was implemented by using a flow probe equipped with 1/16” PFA tubing serving as a flow cell. This was hyphenated to the reactor within a thermostated bypass to maintain process conditions in the transfer lines. Partial least squares regression (PLSR) models were established based on the initial spectra after activation of the reaction with syngas for the prediction of unknown concentrations of 1-dodecene and n-tridecanal over the course of the reaction in the lab-scale system. The obtained Raman spectra do not only contain information on the chemical composition but are further affected by the emulsion properties of the mixtures, which depend on the phase state and the type of micelles. Based on the spectral signature of both Raman and NMR spectra, it could be deduced that especially in reaction mixtures with high 1-dodecene content the formation of isomers as a competitive reaction was dominating. Similar trends were also observed during some of the process runs in the mini-plant. The multivariate calibration allowed for the estimation of reactants and products of the hydroformylation reaction in both laboratory setup and mini-plant. T2 - 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017) CY - Potsdam, Germany DA - 10.05.2017 KW - Microemulsions KW - Process Analytical Technology KW - Reaction Monitoring KW - Online NMR Spectroscopy KW - Online Raman Spectroscopy PY - 2017 SP - 64 EP - 64 CY - Frankfurt a. M. AN - OPUS4-40228 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Paul, Andrea A1 - Wander, Lukas A1 - Gräßer, Patrick A1 - Maiwald, Michael T1 - Design and Validation of a Compact NMR Analyser N2 - Monitoring chemical reactions is the key to chemical process control. 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. Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. If these are not available, there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Unionʼs Research Project CONSENS (Integrated Control and Sensing) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method. T2 - 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017) CY - Potsdam, Germany DA - 10.05.2017 KW - Prozessanalytik KW - Reaction Monitoring KW - Online NMR Spectrsocopy KW - Process Analytical Technology KW - Industrie 4.0 KW - EuroPACT PY - 2017 SP - 72 EP - 73 CY - Frankfurt a. M. AN - OPUS4-40229 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Maiwald, Michael A1 - Sperling, M. A1 - Huber, C. A1 - Hayen, H. A1 - Teutenberg, T. A1 - Belder, D. A1 - Karst, U. A1 - Hagenhoff, B. A1 - Vogel, M. T1 - Prozessanalytik: Spektroskopie und Miniaturisierung N2 - Forderungen nach höherer Geschwindigkeit und die Komplexität der Fragen geben der analytischen Chemie neue Impulse. So nutzt die Prozessanalytik gepulste Ramanspektrometer, die Elemente Arsen und Quecksilber dominieren die Forschung in der Speziesanalytik, und die Omics-Techniken entwickeln sich zu Multi-Omics-Ansätzen. Ambiente MS-Techniken benötigen keine aufwendige Probenvorbereitung, multidimensionale Trenntechniken werden verstärkt in der Routine eingesetzt, und Chip-basierte Trennungen fallen durch Schnelligkeit auf. Molekülspektroskopie und Massenspektrometrie dominieren die bildgebenden Verfahren, und die Lateralauflösung der ToF-Sekundärionenmassenspektrometrie hat sich bei Oberflächenuntersuchungen verbessert. KW - Prozessanalytik KW - Quanten-Kaskadenlaser KW - Photonendichtewellen-Spektroskopie KW - Gepulste Ramanspektrometer KW - Partikelmesstechnik KW - Prozesssensoren PY - 2016 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-361371 UR - http://onlinelibrary.wiley.com/doi/10.1002/nadc.20164046080/abstract DO - https://doi.org/10.1002/nadc.20164046080 SN - 1868-0054 VL - 64 IS - 5 SP - 497 EP - 508 PB - Wiley-VCH Verlag GmbH & Co. KGaA CY - Weinheim AN - OPUS4-36137 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Zientek, Nicolai A1 - Meyer, Klas A1 - Kern, Simon T1 - Low field NMR spectroscopy for online monitoring N2 - Online NMR spectroscopy is an excellent tool to study complex reacting multicomponent mixtures and gain process insight and understanding. For online studies under process conditions, flow NMR probes can be used in a wide range of temperature and pressure. This paper compiles the most important aspects towards quantitative process NMR spectroscopy in complex multicomponent mixtures and provides examples. After NMR spectroscopy is introduced as an online method and for technical samples without sample preparation in deuterated solvents, influences of the residence time distribution, pre-magnetization, and cell design are discussed. NMR acquisition and processing parameters as well as data preparation methods are presented and the most practical data analysis strategies are introduced. T2 - Sonderkolloquium der INVITE-GmbH CY - Leverkusen, Germany DA - 07.09.2016 KW - Industrie 4.0 KW - CONSENS KW - Prozessanalytik KW - Online NMR spectroscopy PY - 2015 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-361417 AN - OPUS4-36141 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Zientek, Nicolai A1 - Laurain, Clement A1 - Meyer, Klas A1 - Paul, Andrea A1 - Engel, D. A1 - Kraume, M. A1 - Guthausen, G. T1 - Automated Data Evaluation and Modeling of Simultaneous 19F-1 H Benchtop NMR Spectra for Online Reactin Monitoring N2 - Benchtop nuclear magnetic resonance spectroscopy currently develops to an important analytical tool for both quality control and process monitoring. In contrast to high resolution online NMR (HR-NMR), benchtop NMR can be operated under rough environmental conditions. A continuous re-circulating stream of reaction mixture from the reaction vessel to the NMR spectrometer enables a non-invasive, volume integrating online analyses of reactants and products. Here we investigated the esterification of 2,2,2-trifluoroethanol with acetic acid to 2,2,2-trifluoroethyl acetate both by 1H HR-NMR (500 MHz) and 1H and 19F MR NMR (43 MHz and 40 MHz) as a model system. The parallel online measurement was realized by splitting the flow, which allowed the adjustment of quantitative and independent flow rates, both in the benchtop NMR probe as well as in the HR-NMR probe, in ad-dition to a fast bypass line back to the reactor. T2 - SMASH 2015 (Small Molecules NMR Conference) CY - Baveno, Italy DA - 20.09.2015 PY - 2015 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-351645 AN - OPUS4-35164 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon T1 - Innen hui und außen pfui – Smarte Prozess-Sensoren in der gegenwärtigen Automatisierungslandschaft der Prozessindustrie N2 - Prozess-Sensoren 4.0 vereinfachen ihre Einbindung über Plug and Play, obwohl sie komplexer werden. Sie bieten Selbstdiagnose, Selbstkalibrierung und erleichterte Parametrierung. Über die Konnektivität ermöglichen die Prozess-Sensoren den Austausch ihrer Informationen als Cyber-physische Systeme mit anderen Prozess-Sensoren und im Netzwerk. Der Wandel von der aktuellen Automation zum smarten Sensor ist im vollen Gange. Automatisierungstechnik und Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. Eine Topologie für smarte Sensoren, die das Zusammenwirken mit daten- und modellbasierte Steuerungen bis hin zur Softsensorik beschreibt gibt es heute jedoch noch nicht. Wir müssen jetzt schnell die Weichen für eine smarte und sichere Kommunikationsarchitektur stellen, um zu einer störungsfreien Kommunikation aller Komponenten auf Basis eines einheitlichen Protokolls zu kommen. Unnötiges Schnickschnack ist nicht erwünscht. Wenn die Prozessindustrie dieses nicht definiert, tun es andere. Für die weitere Entwicklung von der Ist‐Situation zu einer Industrie-4.0-Welt in der Prozessindustrie werden mehrere Szenarien diskutiert. Diese reichen vom erleichterten Abruf sensorbezogener Daten über zusätzliche Kommunikationskanäle zwischen Sensor und mobilen Endgeräten über vollständig bidirektionale Kommunikation bis hin zur Einbindung der Cloud und des Internets in virtualisierte Umgebungen. Um zu einer störungsfreien Kommunikation aller Komponenten untereinander zu kommen, muss mindestens ein einheitliches Protokoll her, das alle sprechen und verstehen. Der derzeit greifbarste offengelegte Standard, der moderne Kommunikationsanforderungen erfüllt, ist OPC Unified Architecture (OPC-UA). Viele halten das Sortieren der Kommunikationsstandards für eines der wesentlichen Errungenschaften von Industrie 4.0. Der Vortrag greift die Anforderungen der Technologie-Roadmap „Prozess-Sensoren 4.0“ auf und zeigt Möglichkeiten zu ihrer Realisierung am Beispiel eines Online-NMR-Analysators, der im Rahmen des EU-Projekts „CONSENS“ (www.consens-spire.eu) entwickelt wurde. Aktuelle und zukünftige öffentliche Förderung von Industrie 4.0-Projekten sind eine gute Investition. Wegen der hohen Komplexität und Interdisziplinarität gelingt die Umsetzung nur gemeinsam zwischen Anwendern aus der Prozessindustrie, Software- und Geräteherstellern sowie Forschungsgruppen. Anwender sind gefragt, diese neue Technologie durch eine beschleunigte Validierung und Akzeptanz umzusetzen. Sie erhalten die einzigartige Chance, ihre Prozesse und Anlagen wettbewerbsfähig zu halten. Kooperativ betriebenen F&E-Zentren und gemeinsam anerkannten Applikationslaboren kommt dafür eine hohe Bedeutung zu. T2 - 13. Dresdner Sensor Symposium CY - Dresden, Germany DA - 04.12.2017 KW - Prozessanalytik KW - Prozess-Sensoren 4.0 KW - Online-NMR-Spektroskopie KW - Continuous Manufacturing KW - Process Analytical Technology KW - CONSENS PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-432056 AN - OPUS4-43205 LA - deu 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 will simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. This is particularly important for concepts like self-diagnostics, self-calibration and self-configuration/parameterization. Intelligent field devices as parts of digital field networks, Inter-net Protocol (IP)-based connectivity and web interfaces, as well as advanced data analysis soft-ware will provide the basis for future projects like Industrie 4.0, Factory of the Future, or Industrial Internet of Things (IIoT). The talk summarizes the currently discussed general requirements for process sensors 4.0 and introduces an online NMR sensor as example. This sensor was developed to provide integrated control and sensing for sustainable operation of flexible intensified processes (CONSENS) funded by the European Union’s Horizon 2020 research and innovation programme. T2 - Eurosensors 2017 Conference CY - Paris, France DA - 03.09.2017 KW - Process Monitoring KW - Smart Sensors KW - Online NMR Spectroscopy KW - Indirect Hard Modeling KW - Industrie 4.0 KW - Eurosensors PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-418271 UR - http://www.eurosensors2017.eu/ AN - OPUS4-41827 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Kern, Simon A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Paul, Andrea A1 - Wander, Lukas T1 - Design and validation of a compact online NMR module N2 - Monitoring chemical reactions is the key to process control. Today, mainly optical online methods are applied, which are calibration intensive. NMR spectroscopy has a high potential for direct loop process control while cutting the calibration and validation needs to an minimum and thus exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control. Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. Data analysis techniques are available but currently mostly used for off-line data analysis to detect the causes of variations in the product quality. This is addressed within the EU’s Research Project CONSENS by the development and integration of a smart NMR module for process monitoring. The presented NMR module is provided in a mobile explosion proof housing and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation. Such “smart sensors” provide the basis for the future project “Industrie 4.0”, and Industrial Internet of Things (IIoT), along with current requirements to process control, model based control, or soft sensing. The module transforms the acquired online spectra of various technically relevant reactions to either conventional 4‒20 mA signals as well as WiFi based OPC-UA communication protocols, which enables NMR-based advanced process control and funny discussions with plant managers along with automation and safety engineers. T2 - Small Molecule NMR Conference (SMASH) CY - Baveno, Italy DA - 17.09.2017 KW - Online NMR spectroscopy KW - CONSENS KW - Reaction monitoring KW - Process control KW - Process analytical technology KW - Indirect hard modeling KW - Industrie 4.0 KW - Smart sensors KW - SMASH PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-419473 UR - http://www.smashnmr.org/conference/program AN - OPUS4-41947 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kern, Simon A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gräßer, Patrick A1 - Paul, Andrea A1 - King, R. A1 - Maiwald, Michael T1 - Online low-field NMR spectroscopy for process control of an industrial lithiation reaction—automated data analysis N2 - Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies. We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (Indirect Hard Modelling – IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union’s Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analysed by IHM with low calibration effort, compared to a multivariate PLS-R (Partial Least Squares Regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy. KW - Online NMR spectroscopy KW - Process analytical technology KW - Partial Least Squares Regression KW - Indirect Hard Modeling KW - Benchtop NMR Spectroscopy KW - Smart Sensors KW - CONSENS PY - 2018 UR - https://link.springer.com/article/10.1007/s00216-018-1020-z DO - https://doi.org/10.1007/s00216-018-1020-z SN - 1618-2642 SN - 1618-2650 VL - 410 IS - 14 SP - 3349 EP - 3360 PB - Springer CY - Berlin, Heidelberg AN - OPUS4-44847 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Aktuelle Herausforderungen für die Prozessanalytik – von der Online-NMR-Spektroskopie im Feld bis zum Plasmaspektrometer auf dem Acker N2 - Der Vortrag stellt einige aktuelle Herausforderungen für die Prozessanalytik und mögliche Antworten vor. Gepulste Raman-Spektrometer akkumulieren das Raman-Signal mit Hilfe schneller optischer Schalter im Picosekunden-Bereich, bevor langlebigere Fluoreszenzanregung entsteht. Damit lassen sich stark fluoreszierende Materialien untersuchen, die bislang nicht zugänglich sind. Eine weitere interessante Entwicklung ist etwa die Shifted excitation Raman difference spectroscopy (SERDS) die besonders für biologische Anwendungen interessant ist. Flexible, modulare Produktionsanlagen stellen einen vielversprechenden Ansatz für die kontinuierliche Produktion von Fein- und Spezialchemikalien dar. In einem EU-Projekt wurde die Feldintegration eines Online-NMR-Sensormoduls als smartes Modul für die Prozesskontrolle vorangebracht. Dieses Modul basiert auf einem kommerziell erhältlichen Niederfeld-NMR-Spektrometer, welche zurzeit für die Anwendung im Laborbereich erhältlich ist. Für die Feldintegration wurde ein ATEX-zertifiziertes, explosionsgeschütztes Gehäuse entwickelt sowie Automationsschemen für den unbeaufsichtigten Betrieb und für die kalibrierfreie spektrale Datenauswertung erstellt. Eine sehr gut anwendbare analytische Messtechnik zur Kontrolle der elementaren Zusammensetzung von verschiedensten Materialien ist die laserinduzierte Plasmaspektroskopie (LIPS, engl. LIBS - Laser-induced Breakdown Spectroscopy). Bei der LIBS wird ein kurz gepulster Laser auf eine Probe fokussiert, um ein Leuchtplasma zu erzeugen. Das dabei erzeugte Atomemissionsspektrum ermöglicht eine qualitative und quantitative Analyse der Zusammensetzung der Probe bezüglich praktisch aller Elemente des Periodensystems. In einem aktuellen Projekt wird diese Methode neben anderen zur Online-Analyse von Ackerböden für die ortsspezifischer Bewirtschaftung (Precision Agriculture) weiterentwickelt und bewertet. T2 - Seminar der Institute Analytische Chemie CY - Universität Duisburg-Essen, Essen, Germany DA - 23.04.2018 KW - Prozessanalytik KW - Time-gated Raman-Spektroskpie KW - Online-NMR-Spektroskopie KW - Laser-induced Breakdown Spectroscopy KW - Online-RFA-Spektroskopie PY - 2018 AN - OPUS4-44754 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana 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. The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control giving an overview from direct dissolution studies of API cocrystals to studies of emulsions for a hydroformylation. T2 - Boston and Cambridge NMR community seminar CY - Cambridge, MS, USA DA - 02.03.2018 KW - Process Monitoring KW - Process Control KW - Pprocess analytical technology KW - Indirect Hard Modeling KW - Spectral Modeling KW - CONSENS PY - 2018 AN - OPUS4-44348 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Cyber-physical Testlabs: Anforderungen an modulare Labore im Zeitalter der Digitalisierung N2 - Von der zunehmenden Digitalisierung sind alle Bereiche von Wirtschaft, Industrie und Gesellschaft betroffen. Die Digitalisierung führt zu einer verstärkten virtuellen Nutzung von Ressourcen und zu einer hochdynamischen Entwicklung der zugehörigen Forschungs- und Technologiefelder. Neue Technologien sind die Basis für die erfolgreiche Weiterentwicklung des Wirtschaftsstandortes Deutschland und für eine Wertschöpfung in globalen Märkten. Die nachhaltige Sicherheit neuer Technologien schafft das Vertrauen der Bürger in den Wandel und sichert unsere Zukunft. Im Vortrag werden Anforderungen und Lösungsvorschläge für das Labor der Zukunft diskutiert. Industrie 4.0 bzw. das Labor 4.0 hilft uns, komplexere Prozesse schneller umzusetzen. Entwicklung von Anlagen und Prozessen beginnt im Labor 4.0. Dazu werden offene, nicht proprietäre Schnittstellen und Standards bei Laborgeräten und Feldgeräten dringend benötigt. Der Standard OPC-UA wird derzeit als gesetzt gesehen. Als nächstes ist die Festlegung der Semantik (Companion Specification) erfordert. Als Bitte an die Zulieferer und Geräterhersteller wird gerichtet, möglichst keine Alleingänge hinsichtlich Schnittstellen, Standards oder GUI zu unternehmen, sondern diese mit den Anwendern abzustimmen. Auf diese Weise ergibt sich das in Industrie 4.0 geforderte "durchgehende Engineering“. Die Sicherung der Wettbewerbsfähigkeit des Standorts Deutschland/Europa ergibt sich dann gleich in doppelter Hinsicht: Sichere, verfügbare und effiziente Herstellung international wettbewerbsfähiger Produkte für die Anwender sowie weltweiter Export von Mess- und Regeltechnik für die Messtechnikbranche. T2 - Analytica Expertenpanel: IoT im Labor 4.0 - Laborgeräte auf dem Weg zu Smart Devices CY - München, Germany DA - 11.04.2018 KW - Smarte Feldgeräte KW - Cyber-physical Test Labs KW - Industrie 4.0 KW - Cyberphysisches Labor PY - 2018 AN - OPUS4-44679 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Anforderungen der Prozessindustrie an Gerätekommunikation N2 - Der Vortrag gibt einen Überblick über die aktuellen Diskussionen zu Feldgerätekommunikation in der Prozessindustrie. Diese verfolgt seitens der Anwender in der NAMUR das NOA-Konzept (NOA = NAMUR Open Architecture). In gemeinsamen Aktivitäten mit dem ZVEI werden mit Zielstellung Mitte/Ende 2019 folgende Konzepte vorangebracht: NOA Informationsmodell in OPC UA, Informationssicherheit und das Konzept des „Verification of Request“. Gemeinsam mit Geräte- und Softwareherstellern sollen auch M+O-Sensoren (Maintenance und Optimization) konzipiert werden. Aus dem NAMUR AK 3.7 heraus wurde im Oktober ein Erweiterter Arbeitskreis „Smarte Sensoren, Aktoren und Kommunikation“ kontituiert, dem auch Geräte- und Softwarehersteller und das BSI angehören. Hier werden konkrete Anwendungsfälle für smarte Feldgeräte und Anforderungen an M+O-Sensoren erarbeitet, um die Bereitstellung und den Einsatz smarter Automatisierungskomponenten zu beschleunigen. Zukünftig werden das „Smarte Labor“ und die „Smarte Produktion“ stärker zusammenwachsen. T2 - 5. Sitzung Projektgruppe „Vernetzte Laborgeräte“ SPECTARIS e.V., Berlin CY - Berlin, Germany DA - 14.11.2018 KW - Prozessindustrie KW - Digitalisierung KW - Industrie 4.0 KW - NAMUR Open Architecture (NOA) KW - M+O-Sensoren KW - Spectaris PY - 2018 AN - OPUS4-46586 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Smarte Feldgeräte – Nur "Smartisiert" oder Echte Chance für die Zukünftige Automatisierung? N2 - Um in einem veränderten Umfeld erfolgreich bestehen zu können, müssen Chemieunternehmen neue Pfade beschreiten. Dazu gehört insbesondere das Potential digitaler Technologien. Die volle Integration und intelligente Vernetzung von Systemen und Prozessen kommt zögerlich voran. Dieser Vortrag ist ein Loblied auf die Feldebene. Er möchte dazu ermutigen, die Digitalisierung der Prozessindustrie auf Basis smarter Sensorik, Aktorik und Kommunikation ganzheitlicher zu denken und informiert über aktuelle technische Perspektiven, wie das „Ein-Netzwerk-Paradigma“, Ad-hoc-Vernetzungen, Edge-Computing, FPGAs, virtuelle Maschinen oder Blockchain. Diese geben smarter Sensorik, Aktorik und Kommunikation eine völlig neue Perspektive. N2 - To successfully survive in a changing environment, chemical companies must find new paths. The potential of digital technologies belongs to these. A full integration and intelligent interconnection of systems and processes progresses only hesitantly. This talk is a hymn on the field level. It should encourage to 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”, ad-hoc connections, edge computing, FPGAs, virtual machines and blockchain. These give smart sensors, actuators, and communication a new perspective. T2 - Smart Field Devices – Just „smartified“ or a Real Chance for Future Automation? T2 - NAMUR Hauptsitzung 2018 CY - Bad Neuenahr, Germany DA - 08.11.2018 KW - Smarte Feldgeräte KW - Sensorik KW - Digitalisierung KW - Edge Computing KW - Dezentrale Netzwerke KW - NAMUR PY - 2018 AN - OPUS4-46559 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Workshop: Basic Statistics for NMR N2 - qNMR provides the most universally applicable form of direct concentration or purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. The workshop presents basic terms of statistics and uncertainty analysis, which are the basis for qNMR spectroscopy and data analysis such as, e.g., standard deviations, linear regression, significance tests, etc. and gives typical examples of applications in qNMR spectroscopy. T2 - qNMR-Summit 2018 CY - Würzburg, Germany DA - 10.10.2018 KW - Quantitative NMR Spectroscopy KW - Statistics KW - Quality Assurance KW - NMR validation KW - qNMR PY - 2018 AN - OPUS4-46368 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Compact NMR Spectroscopy: A Versatile Tool for Automated Continuous-Flow Production of Chemicals and Pharmaceuticals N2 - 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 and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated 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. In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals. T2 - Seminar of Research Department „Life, Light & Matter“ of the InterdisciplinaryFaculty of the University of Rostock CY - Rostock, Germany DA - 08.01.2019 KW - Process Analytical Technology KW - Low-field NMR Spectroscopy KW - Online NMR Spectroscopy KW - Modular Production KW - Process Industry KW - Fresenius Lecture PY - 2019 AN - OPUS4-47166 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Meyer, Klas A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Bornemann-Pfeiffer, Martin A1 - Paul, Andrea A1 - Kern, Simon T1 - NMR Spectroscopy for Online Monitoring and Process Control 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. The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control. T2 - Lonza Shared Best Practice Seminar CY - Visp, Switzerland DA - 26.02.2019 KW - Process Analytical Technology KW - Reaction Monitoring KW - Online NMR Spectroscopy KW - Compact NMR Spectroscopy KW - Quantitative NMR Spectroscopy PY - 2019 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-47453 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Kern, Simon A1 - Bornemann-Pfeiffer, Martin A1 - Guhl, Svetlana A1 - Wander, Lukas A1 - Meyer, Klas A1 - Paul, Andrea T1 - How online NMR spectroscopy accelerates chemical process development and manufacturing – From automated spectral analysis to integrated NMR micro reactors N2 - Accelerating chemical process development and manufacturing along with quick adaption to changing customer needs means consequent transformation of former batch to continuous (modular) manufacturing processes. These are justified by an improved process control through smaller volumes, better heat transfer, and faster dynamics of the examined reaction systems. As an example, for such modular process units we present the design and validation of an integrated nuclear magnetic resonance (NMR) micro mixer tailor‐made for a desired chemical reaction based on computational modelling. The micro mixer represents an integrated modular production unit as an example for the most important class of continuous reactors. The quantitative online NMR sensor represents a smart process analytical field device providing rapid and non‐invasive chemical composition information without need for calibration. We describe the custom design 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 an esterification reaction as an example for a chemical reaction process. Systems utilizing such an online NMR analyser benefits through short development and set‐up times based on “modular” spectral models. Such models can simply be built upon pure component NMR spectra within minutes to a few hours (i.e., assignment of the NMR signals to the components) instead of tedious DoE calibrations runs. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). The approach was validated for typical industrial reactions, such as hydrogenations or lithiations. This work wants to show the benefit of NMR spectroscopy as online analytical technique in industrial applications for improving process understanding and efficiency. Especially development and set‐up times based on “modular” data analysis models will enable new production concepts, which are currently discussed with respect to digitization of process industry. PANIC is the ideal forum for such discussions in the application of NMR spectroscopy and its data analysis to the everyday problems in process industry. T2 - Practical Applicatiions of NMR in Industry Conference (PANIC) 2019 CY - Hilton Head Island, USA DA - 04.03.2019 KW - Process Analytical Technology KW - Reaction Monitoring KW - Online NMR Spectroscopy KW - Micro Reactor KW - Data Analysis KW - PANIC PY - 2019 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-47488 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Die Digitalisierung der Prozessindustrie – Voll integrierte und intelligent vernetzte Sensoren und Prozesse für die kontinuierliche Produktion von Chemikalien und Pharmazeutika N2 - Um in einem veränderten Umfeld erfolgreich bestehen zu können, müssen Chemie-unternehmen neue Pfade beschreiten. Dazu gehört insbesondere das Potential digi-taler Technologien. Mit flexiblen, modularen chemischen Vielzweck-Produktionsanlagen lassen sich häufig wechselnde Produkte mit kürzeren Vorlauf- und Stillstandzeiten zwischen den Kampagnen und dennoch hoher Qualität realisie-ren. Intensivierte, kontinuierliche Produktionsanlagen erlauben auch den Umgang mit schwierig zu handhabenden Substanzen. Grundvoraussetzung für solche Konzepte ist eine hochautomatisierte "chemische" Prozesskontrolle zusammen mit Echtzeit-Qualitätskotrolle, die "chemische" Informati-onen über den Prozess bereitstellt. In einem Anwendungsbeispiel wurde eine phar-mazeutische Lithiierungsreaktion aus einer modularen Pilot-Anlage betrachtet und dabei die Vorzüge eines vollautomatischen NMR-Sensors untersucht. Dazu wurde ein kommerziell erhältliches Benchtop-NMR-Spektrometer mit Permanentmagnet auf die industriellen Anforderungen, wie Explosionsschutz, Feldkommunikation und voll-automatischer, robuster Datenauswertung angepasst. Der NMR-Sensor konnte schließlich erfolgreich im vollautomatischen Betrieb nach fortschrittlichen Regelkon-zepten und für die Echtzeitoptimierung der Anlage getestet werden. Die NMR-Spektroskopie erwies sich als hervorragende Online-Methode und konnte zusammen mit einer modularen Datenauswertung sehr flexibel genutzt werden. Die Methode konnte überdies als zuverlässige Referenzmethode zur Kalibrierung konventioneller Online-Analytik eingesetzt werden. Zukünftig werden voll integrierte und intelligent vernetzte "smarte" Sensoren und Pro-zesse eine kontinuierliche Produktion von Chemikalien und Pharmazeutika mit ver-tretbaren Qualitätskosten möglich machen. T2 - ANAKON 2019 CY - Münster, Germany DA - 25.03.2019 KW - Digitalisierung KW - Datenauswertung KW - Digitaler Zwilling KW - Prozessindustrie KW - Prozessanalytik PY - 2019 AN - OPUS4-47650 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Maiwald, Michael T1 - NMR Validation - Measurement Uncertainty N2 - There is a need within the NMR community to progress forward in exploring new facets in which we can use analytical techniques to advance our understanding of various systems. One aspect the NMR community hasn’t fully encompassed is the validation process, which also involves setting reference standards, establishing a common language that directly relates to NMR, communication relating to validation, and much more. This workshopcontribution starts with an overview on international metrology for qNMR spectroscopy. Since NMR is completely described by mathematical equations, the measurement unceartainty can directly be dreived from formula. Examples are presented. These are differentiated between type A and B evaluations. Finally the Expanded Unceartainty is defined. Since the user needs a risk-based unceartainty assessment, different "leagues" for routine, advanced, and high level needs are proposed to make clear, that no all sources of uncertainty have to be taken in considerention at practical levels. T2 - Practical Applications of NMR in Industry Conference (PANIC) 2019 - Validation Workshop CY - Hilton Head Island, USA DA - 04.03.2019 KW - Quantitative NMR Spectroscopy KW - qNMR KW - Uncertainty Evaluation KW - Weighing Uncertainty KW - NMR Method Validation PY - 2019 AN - OPUS4-47509 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Meyer, Klas A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Kern, Simon A1 - Müller, S. A1 - Kowarik, Stefan T1 - Künstliche Neuronale Netze für quantitative Online-Spektroskopie in der Prozessindustrie – Lästige Modellbildung ade? N2 - Bei Industry 4.0 dreht sich alles um Interkonnektivität, sensorgestützte Prozesssteuerung und datengesteuerte Systeme. Prozessanalysentechnik (PAT) wie die Online-Kernresonanzspektroskopie (NMR) gewinnt zunehmend an Bedeutung, da sie zur Automatisierung und Digitalisierung in der Produktion beiträgt. Eine klassische Auswertung von Prozessdaten und deren Umsetzung in Wissen ist jedoch bisher in vielen Fällen aufgrund der unzureichend großen verfügbaren Datensätze nicht möglich oder nicht wirtschaftlich. Bei der Entwicklung eines automatisierten Verfahrens für die Prozesskontrolle stehen manchmal nur die Basisdaten einer begrenzten Anzahl von Batch-Versuchen aus typischen Produkt- und Prozessentwicklungskampagnen zur Verfügung. Diese Datensätze sind jedoch nicht groß genug, um maschinengestützte Verfahren zu trainieren. Um diese Einschränkung zu überwinden, wurde ein neues Verfahren entwickelt, das eine physikalisch motivierte Multiplikation der verfügbaren Referenzdaten erlaubt, um einen ausreichend großen Datensatz für das Training von maschinellen Lernalgorithmen zu erhalten. Das zugrundeliegende Beispiel einer chemischen Synthese wurde spektroskopisch verfolgt und mit der neuen Methode sowie mit einem physikalisch basierten Modell analysiert, wobei sowohl eine anwendungsrelevante Niederfeld-NMR als auch eine Hochfeld-NMR-Spektroskopie als Referenzmethode verwendet wurde. Künstliche neuronale Netze (ANNs) haben das Potenzial, bereits aus relativ begrenzten Eingabedaten wertvolle Prozessinformationen abzuleiten. Um jedoch die Konzentration unter komplexen Bedingungen (viele Edukte und weite Konzentrationsbereiche) vorherzusagen, sind größere ANNs und damit ein größerer Trainingsdatensatz erforderlich. Wir zeigen, dass ein mäßig komplexes Problem mit vier Edukten unter Verwendung von ANNs in Kombination mit der vorgestellten PAT-Methode (Niederfeld-NMR-Spektroskopie) und mit dem vorgeschlagenen Ansatz zur Erzeugung aussagekräftiger Trainingsdaten bewältigt werden kann. T2 - 16. Kolloquium Arbeitskreis Prozessanalytik CY - Online meeting DA - 23.11.2020 KW - Prozessindustrie KW - Online-NMR-Spektroskopie KW - Industrie 4.0 KW - Künstliche Neuronale Netze KW - Prozessanalytik KW - Digitale Transformation PY - 2020 AN - OPUS4-51647 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Aktuelles zur Technologie-Roadmap "Prozess-Sensoren 4.0" N2 - Die auf der NAMUR Hauptsitzung 2015 vorgestellte Technologie-Roadmap „Prozess-Sensoren 4.0“ zeigt die damaligen Anforderungen an Prozess-Sensoren sowie an deren Kommunikations-fähigkeiten auf. Wir berichten über die Umsetzungen der damaligen Ideen/Thesen aus heutiger Sicht und blicken nach vorn. T2 - Workshop NAMUR-Hauptsitzung 2020 CY - Online meeting DA - 05.11.2020 KW - Prozessindustrie KW - Technologie-Roadmap "Prozess-Sensoren 4.0" KW - NAMUR KW - Automation KW - Prozessanalytik KW - Sensoren PY - 2020 AN - OPUS4-51523 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Peters, Claudia A1 - Meyer, Klas T1 - Interlaboratory comparison of benchtop NMR spectrometers – Purities at 200 and 10 mmol/L N2 - Due to its advantages of being a direct comparison method, quantitative NMR spectroscopy (qNMR) becomes more and more popular in industry. While conventional high-field NMR systems are often associated with high investment and operational costs, the upcoming market of permanent-magnet based benchtop NMR systems show a considerable option for a lot of applications. The mobility of these systems allows to bring them more closely to the real production environment, e.g. for at-line quality control. In this work we present an interlaboratory comparison study investigating the qNMR performance of state-of-the-art benchtop NMR spectrometers. Therefore, BAM prepared two samples of a mixture of NMR reference standards tetramethylbenzene (TMB) and tetrachloronitrobenzene (TCNB) at concentration levels of 200 mM and 10 mM. These “ready-to-use” samples were sent to participant laboratories, which performed analysis on their benchtop NMR equipment of different vendors and fields from 43 to 80 MHz. Raw data was reported back and further investigated by using different data analysis methods at BAM. After this very first qNMR comparison study of benchtop NMR spectrometers show promising results, following studies are planned to cover more parts of the qNMR process, e.g. sample preparation and weighing, but also data analysis, as commonly done in similar studies for high-field NMR spectroscopy in industry and metrology. T2 - The United States Pharmacopeial Convention (USP) Emerging Technologies Workshop & Roundtable CY - Online meeting DA - 17.11.2020 KW - Quantitative NMR Spectroscopy KW - QNMR KW - Purity KW - Interlaboratory Comparison KW - Low-field NMR Spectroscopy PY - 2020 UR - https://www.cvent.com/events/emerging-technologies-workshop-roundtable-quantitative-nmr-and-digital-data-applications-overview-an/event-summary-f128e4bfbedc48d6946f554ea719d6b1.aspx?dvce=1 AN - OPUS4-51526 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Fricke, F. A1 - Mahmood, S. A1 - Hoffmann, J. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, Stefan A1 - Westerdicky, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. T2 - 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) CY - Online meeting DA - 01.02.2021 KW - Industry 4.0 KW - Cyber-Physical Systems KW - Artificial Neural Networks KW - Mass Spectrometry KW - Nuclear Magnetic Resonance Spectroscopy PY - 2021 UR - www.date-conference.com SN - 978-3-9819263-5-4 SP - 615 EP - 620 PB - Research Publishing AN - OPUS4-52180 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Meyer, Klas A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Kern, Simon A1 - Müller, S. A1 - Kowarik, Stefan T1 - Integrated and Networked Systems and Processes – A Perspective for Digital Transformation in (Bio) Process Engineering N2 - The competitiveness of the process industry is based on ensuring the required product quality while making optimum use of equipment, raw materials and energy. Chemical 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. One way is knowledge-based production, taking into account all essential equipment, process and regulatory data of plants and laboratories. Today, the potential of this data is often not yet consistently used for a comprehensive understanding of production. Another approach uses flexible and modular chemical plants, 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. Digital transformation is enabling completely new production concepts that are being used increasingly. Intensified continuous production plants also allow for difficult to produce compounds. This contribution aims to encourage a more holistic approach to the digitalization and use of machine-assisted methods in (bio) process engineering by introduction of integrated and networked systems and processes, which have the potential to speed up the high-quality production of specialty chemicals and pharmaceuticals. T2 - 6th BioProScale Symposium - industrial scale bioprocess intensification from process development to large-scale understanding CY - Online meeting DA - 29.03.2021 KW - Industry 4.0 KW - Biotechnology KW - Bio engineering KW - Process Analytical Technology KW - BioProScale KW - Artificial Neural Networks PY - 2021 UR - https://biotechnologie.ifgb.de/node/648 AN - OPUS4-52371 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Maiwald, Michael ED - Tauschnitz, T. T1 - Erweiterung des NOA-Konzepts - M+O-Sensoren, NE 183 N2 - Der Sensorik kommt bei der Digitalisierung der Prozessindustrie eine Schlüsselrolle zu. Entsprechend ist sie ein zentraler Baustein der NAMUR Open Architecture Konzepts (NOA). M+O-Sensoren (Monitoring + Optimization) - stellen eine neue Geräteklasse für die zusätzliche Überwachung und Optimierung von Anlagen der Prozessindustrie dar. Diese deckt klassische und alternative Messprinzipien bis hin zur Nachbildung der menschlichen Sinne ab. Hier werden die Anforderungen an M+O-Sensoren als Bestandteile der NOA beschrieben. KW - Prozessanalytik KW - Prozessindustrie KW - Sensoren KW - M+O-Sensoren KW - NAMUR Open Architecture KW - NOA PY - 2021 SN - 978-3-8356-7451-6 SP - 39 EP - 45 PB - Vulkan-Verlag GmbH CY - Essen ET - 1 AN - OPUS4-52912 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Kipphardt, Heinrich A1 - Khanipour, Peyman A1 - Tuma, Dirk T1 - Messverfahren für Wasserstoff: Qualität durch Zertifizierung – Standortvorteile in Deutschland N2 - Die Veranstaltungsreihe "Neue Märkte erschließen – mit Normen und Standards hoch hinaus", die vom DIN gemeinsam mit der NOW GmbH organisiert wird, richtets sich vorwiegend an KMUs. Fokus der Veranstaltung sind Messverfahren für Wasserstoff. Der Beitrag der BAM führt sehr kurz die Rolle nationaler und internationaler Normung sowie weltweiter Metrologie im Rahmen der Meterkonvention bezüglich analytischer Qualitätssicherung und Zertifizierung von Gasen und Referenzmaterialien ein. Es werden aktuelle Beispiele für die Qualitätssicherung von Wasserstoff, mögliche dazu notwendige Ausrüstung und weiterführende Literaturquellen vorgestellt. T2 - Neue Märkte erschließen – mit Normen und Standards hoch hinaus CY - Online meeting DA - 18.03.2021 KW - Wasserstoff KW - Normung KW - Standortvorteil KW - Analytik KW - Wasserstoffanalytik KW - Wasserstoff Referenzmaterial KW - Gasanalytik PY - 2021 AN - OPUS4-52296 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Maiwald, Michael A1 - Klaer, R.-H. A1 - Wagner, A. ED - Kockmann, N. T1 - 100 % Digital in der Prozessindustrie Tutzing-Symposion Teil 3: Intelligente Nutzung von Daten und Bausteinen der Digitalisierung N2 - Digitalisierung und Industrie 4.0 verändern komplette Geschäftsmodelle, heben neue Effizienzpotenziale und stärken die Wettbewerbsfähigkeit. Auf dem 57. Tutzing-Symposion vom 15.–18.04.2018 wurde mit Vorträgen und Kreativworkshops erkundet, welche speziellen Anforderungen die Prozessindustrie hat, welche digitalen Innovationen bereits umgesetzt wurden und wo noch Handlungsbedarf besteht. Ein Workshop befasste sich mit den Themenfeldern Datenkonzepte, Datenanalyse, Big Data und künstliche Intelligenz. KW - Prozessindustrie KW - Digitalisierung KW - Industrie 4.0 KW - Datenanalyse KW - Künstliche Intelligenz PY - 2019 SN - 1436-2597 VL - 22 SP - 14 EP - 19 PB - Wiley-VCH CY - Weinheim AN - OPUS4-48838 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Maiwald, Michael ED - Meyer, Simon T1 - Voll integrierte und vernetzte Systeme und Prozesse - Perspektive: Smarte Sensorik, Aktorik und Kommunikation N2 - Unternehmen der chemischen Industrie müssen neuen Pfade beschreiten, um in einem veränderten Umfeld erfolgreich bestehen zu können. Dazu gehört insbesondere, das Potenzial digitaler Technologien zu nutzen. Die volle Integration und intelligente Vernetzung von Systemen und Prozessen kommt allerdings nur zögerlich voran. Dieser Beitrag ist ein Loblied auf die Feldebene. Er möchte dazu ermutigen, die Digitalisierung der Prozessindustrie auf Basis smarter Sensorik, Aktorik und Kommunikation ganzheitlicher zu denken und informiert über aktuelle technische Perspektiven, wie das Ein-Netzwerk-Paradigma, Ad-hoc-Vernetzungen, Edge-Computing, FPGAs, virtuelle Maschinen oder Blockchain. Diese geben smarter Sensorik, Aktorik und Kommunikation eine völlig neue Perspektive. KW - Smarte Sensoren KW - Smarte Aktoren KW - Digitalisierung KW - Prozessindustrie KW - Prozess-Sensoren 4.0 PY - 2019 SN - 978-3-8356-7436-3 SP - 28 EP - 40 PB - Vulkan-Verlag GmbH CY - Essen AN - OPUS4-50035 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Compact NMR Spectroscopy: A Versatile Tool for Automated Continuous-Flow Production of Chemicals and Pharmaceuticals N2 - 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 and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated 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. In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals. T2 - GDCh-Kolloquium der Universität Ulm CY - Ulm, Germany DA - 28.11.2019 KW - Process Analytical Technology KW - Reaction Monitoring KW - Online NMR Spectroscopy KW - Process Industry KW - Automation PY - 2019 AN - OPUS4-49855 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Compact NMR Spectroscopy: A Versatile Tool for Automated Continuous-Flow Production of Chemicals and Pharmaceuticals N2 - 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 and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated 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. In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals. T2 - Global PAT Meeting Bayer AG CY - Berlin, Germany DA - 12.11.2019 KW - Process Analytical Technology KW - Reaction Monitoring KW - Online NMR Spectroscopy KW - CONSENS PY - 2019 AN - OPUS4-49602 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Informationsmanagement in der Prozessindustrie auf Basis von Labor- und Produktionsdaten N2 - Die Wettbewerbsfähigkeit der Prozessindustrie basiert auf der Sicherung der geforderten Produktqualität bei einer optimalen Nutzung von Anlagen, Rohstoffen und Energie. Ein Weg zur wissensbasierten Produktion führt über die Betrachtung der wesentlichen Apparate-, Prozess- und Freigabedaten aus Betrieben und Labors. Das Potenzial dieser Daten wird heute vielfach noch nicht konsequent für ein umfassendes Verständnis der Produktion genutzt. Neben Fragen zur Datenerfassung, Datenkonnektivität und Datenintegrität müssen solche Daten für eine ganzheitliche Prozessanalyse zunächst mit Kontextinformationen zusammengebracht werden. Datenquellen enthalten Zeitwertpaare, aber auch diskrete Daten aus LIMS (Laboratory Information Management Systems) oder ELN (Electronic Laboratory Notebooks) und werden zunehmend durch 2D- und 3D-Daten aus der Chromatographie-Massenspektrometrie oder bildbasierter Analytik ergänzt. Für die automatisierte Merkmalsextraktion, etwa zur Extraktion chemischer Informationen aus den oben genannten Datenquellen werden multivariate Werkzeuge und Algorithmen genutzt. Multivariate Statistiken wie PCA (Principle Component Analysis), PLS (Partial Least Squares) und LDA (Latent Discriminant Analysis) bilden die erste Grundlage für die Datenanalyse. Für diese Verfahren sind heute Datenvorbehandlungsschritte nötig. Die Modellbildung geschieht manuell und ist sehr aufwendig. Können diese Daten im Zeitalter von ML (Machine Learning) und KI (Artificial Intelligence) anderweitig sinnvoll genutzt werden und ohne klassische Modellbildung? Die Bezeichnung „Big Data“ als Voraussetzung für datengetriebene Auswerteverfahren ist für die Prozessindustrie allerdings unpassend, denn auch bei mengenmäßig großen Datensätzen liegen für Kampagnen typischerweise nur Informationen über einige Batches mit einer Serie von Messdaten vor, die genügend Varianz für eine datengetriebene Auswertung aufweisen – nicht vergleichbar mit den Datenmengen im WWW oder von großen Internet-Konzernen. T2 - Bio-PAT-Workshop, Aktuelle Entwicklungen im Bereich PAT & Softsensortechnologien CY - Berlin, Germany DA - 04.12.2019 KW - Prozessindustrie KW - Digitalisierung KW - Datenanalyse KW - Datenvorbehandlung KW - Multivariate Datenanalyse PY - 2019 AN - OPUS4-49942 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -