TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Wander, Lukas A1 - Paul, Andrea A1 - Bremser, Wolfram A1 - Maiwald, Michael T1 - Mathematical and statistical tools for online NMR spectroscopy in chemical processes N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environ¬ments for advanced process monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS. We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes. T2 - Advanced Mathematical and Computational Tools in Metrology and Testing conference CY - Glasgow, United Kingdom DA - 29.08.2017 KW - Online NMR Spectroscopy KW - Process Control KW - Partial Least Squares Regression KW - Indirect Hard Modelling KW - Quantum Mechanics KW - First Principles PY - 2018 SN - 978-9-813-27429-7 VL - 89 SP - 229 EP - 234 PB - World Scientific CY - New Jersey AN - OPUS4-51391 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael 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 - CONF A1 - Maiwald, Michael 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 T1 - Using Smart Sensors and Modular Production Units - For Sustainable and Flexible Production of High Quality Chemicals and Pharmaceuticals 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 also an overview on direct dissolution studies of API cocrystals. T2 - Pfizer Analytical Chemistry Seminar CY - Pfizer Global Research & Development, Groton, CT, USA DA - 01.03.2018 KW - Online NMR Spectroscopy KW - Process sensors KW - Process analytical technology KW - Indirect Hard Modeling KW - Dissolution studies KW - CONSENS PY - 2018 AN - OPUS4-44347 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael 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 - Im Wohnzimmer haben wir es zuerst – Wie Innovationen für den Massenmarkt die Digitalisierung der Prozessindustrie vorantreiben N2 - Automatisierungstechnik, sowie die Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. In der Prozessindustrie tut man sich aber schwer, die heu-te schon möglichen daten- oder modellbasierten Steuerungen auf Basis smarter Sen-soren und Aktoren einzusetzen oder allein Anforderungen daran vorzugeben. Viele aktuelle Entwicklungen der Zulieferer werden verwehrt und man wartet lieber ab. Es bilden sich schon jetzt rasant schnell neue digitale Geschäftsmodelle in der Pro-zessindustrie, wie es schon mit der zunehmenden Verbreitung des Internets beobach-tet werden konnte. Wenn die Automatisierer und Anlagenspezialisten jetzt nicht ge-stalten, tun es andere. Früher war es umgekehrt: Informations- und Kommunikationstechnik für Profis konn-ten sich nur die Großkonzerne leisten. Die Technologie vom Personalcomputer bis zum Smart-Gerät und ihre Peripherie wurden und werden ausschließlich durch den Massenmarkt vorangetrieben. Also müssen wir umdenken und Wege finden, die rasch voranschreitende Informations- und Kommunikationstechnik geschickt für die Digitalisierung umbiegen. Der Beitrag erörtert aktuelle Diskussionen über netzartige Verbindungen der Feldge-räte (Sensoren und Aktoren) untereinander und zur Cloud sowie über virtuelle Server-verbünde und Applikationen, die auf Cloud-Diensten basieren. Mit einem solchen System ist die Einrichtung beliebiger Dienstleistungen und Funktionen auf der Basis der jeweils gängigen Methoden und Technologie des Internets möglich. Beispiele für Dienstleistungen sind beispielsweise auf prozessanalytische oder Sensordaten auf-bauende Instandhaltungsdienste oder Energiedienste für Anlagen. T2 - 14. Kolloquium Prozessanalytik CY - Hannover, Germany DA - 03.12.2018 KW - Digitalisierung KW - Prozessindustrie KW - Prozessanalytik KW - Automatisierung KW - Innovationen KW - Informations- und Kommunikationstechnik PY - 2018 AN - OPUS4-46899 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - The future of analytical sciences: Trends and challenges N2 - What is the future of Analytical Sciences? The talk starts with a definition, comparing the current view with that from 1968. How do wie set trends? How do we get Analytics inside? Some examples of "Big Science" are given and discussed in relation to a definition of AS. How does AS face the current Grand Challenges? As exaples for something significant, several exaples are presented, such as Climate Change of Hydrogen Storage. Another important trand are eScience and automation concepts for AS, which are highlighted. But (Analytical) Science has to be politcal in our times to face Fake News and to breake barriers! T2 - Sonderkolloquium Abteilung 1 "Analytische Chemie; Referenzmaterialien" CY - Berlin, Germany DA - 05.10.2018 KW - Analytical science KW - Grand challenges KW - Big science KW - Fake news KW - Climate change PY - 2018 AN - OPUS4-47285 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 - Guhl, Svetlana A1 - Maiwald, Michael T1 - Produzieren Sie schon oder kalibrieren Sie noch? – Online-NMR-Spektrometer als Smarte Feldgeräte N2 - Der Übergang von der aktuellen Automatisierungslandschaft zur nächsten Generation von Automatisierungskonzepten für die Prozessindustrie hat bereits begonnen. Intelligente Funktionen der Sensoren vereinfachen ihre Anwendung und ermöglichen eine Plug-and-Play-Integration, auch wenn sie auf den ersten Blick komplexer erscheinen mögen. Dies ist die Basis für die Digitalisierung der Prozessindustrie und hilft uns, komplexere Prozesse schneller umzusetzen. Der Vortrag fasst die derzeit diskutierten allgemeinen Anforderungen an „Smarte Feldgeräte“ zusammen und diskutiert dieses am Beispiel eines smarten Online-NMR-Sensors. NMR-Spektroskopie bietet sich durch den Vorteil der direkten Vergleichsmethode (ohne Kalibrierung) für die Prozess-Steuerung an und verringert somit die Rüstzeiten. Zudem basiert der Sensor auf physikalisch motivierten Modellen (Indirect Hard Modeling, IHM), die sich modular kombinieren lassen. Die Methoden wurden anhand eines vorgegebenen pharmazeutischen Reaktionsschrittes im Rahmen des „Horizon 2020“-Projekts CONSENS der Europäischen Union demonstriert und validiert. Zuletzt werden Anforderungen an die Weiterentwicklung der Datenauswertemethoden diskutiert, um letztlich die semantische Information aus den Messdaten herauszulesen oder das in der Industrie 4.0 geforderte „durchgehende Engineering“ für die Automatisierungskomponenten zu ermöglichen. T2 - ProcessNet-Jahrestagung und 33. DECHEMA-Jahrestagung der Biotechnologen CY - Aachen, Germany DA - 10.09.2018 KW - Prozessindustrie KW - Prozessanalytik KW - Online-NMR-Spektroskopie KW - Datenkonzepte KW - Datenanalyse KW - CONSENS PY - 2018 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-45934 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -