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Die chemische Industrie steht derzeit, wie viele andere Industriebereiche, vor den Herausforderungen einer Digitalisierung der Produktion. Sie ist der Schlüssel für die Flexibilisierung von Prozessen und Anlagen, für die Verkürzung von Produkteinführungszeiten sowie für den Zuschnitt der Produktion auf wechselnde Nachfrage und kürzere Produktlebenszyklen. Die Messtechnik und Sensorik spielt neben der intelligenten Datenverarbeitung eine Schlüsselrolle für die Digitalisierung. Flexiblere Anlagen benötigen Sensorik zur Überwachung des Anlagenzustandes, zur Früherkennung nicht bestimmungsgemäßer Betriebszustände sowie für eine bedarfsgerechte Wartung. Da die Entwicklung neuer und verbesserter Messtechnik und Sensorik grundlegend aus verschiedenen Richtungen gedacht werden muss, haben sich Akteure aus verschiedenen Branchen zusammengetan und dieses Positionspapier erstellt. Es basiert auf einer grundlegenden Analyse des Ist-Stands sowie des Bedarfs der Industrie, die unter anderem auf einem eigens dafür durchgeführten Workshop mit Sensorentwicklern, Anlagenherstellern sowie Anlagenbetreibern am 18. Juni 2019 bei der DECHEMA in Frankfurt a. M. diskutiert wurden. Diese Aktivitäten wurden maßgeblich von der Initiative Wanted Technologies der ProcessNet sowie dem AMA Verband für Sensorik und Messtechnik e.V. initiiert.
OPC-UA für Prozessindustrie und Laborwelt - Offener Standard für die störungsfreie Kommuniktaion
(2021)
Im privaten Umfeld machen wir uns keine Gedanken mehr über die Einbindung von elektronischen Geräten in Netzwerke, sei es bei der Verbindung des Mobiltelephons mit dem W-Lan-Netzwerk des Hotels oder von Freunden oder des drahtlosen Kopfhörers mit dem Notebook: Wir erwarten, dass es auf Anhieb funktioniert. Dahinter stecken offene Standards für die Konnektivität.
Dafür braucht man immer zwei Dinge: Einen physischen Kommunikationskanal, auf dem die Datenpakete zwischen den Komponenten und Geräten hin- und herwandern und eine einheitliche Kommunikationssprache, so dass sich die Komponenten und Geräte auch untereinander verstehen, weil sie dieselbe Sprache sprechen und automatisch wissen, was sie miteinander zu besprechen haben. Wenn man eine sichere Konnektivität bevorzugt, werden weitere Informationen benötigt, wie etwa ein Passwort.
Auch für die störungsfreie Kommunikation aller Automatisierungskomponenten der Prozessindustrie untereinander oder etwa für die Kommunikation von Geräten in einem analytischen Labor wird ein einheitliches Protokoll (Kommunikationssprache) und ein einheitlicher Feldbus (Kommunikationskanal) benötigt. Mittlerweile gilt der Standard OPC Unified Architecture (OPC-UA) für das Erstere als gesetzt und kann als ein kleiner Triumph von Industrie 4.0 betrachtet werden. OPC-UA kann auf verschiedenen Kommunikationskanälen laufen – am liebsten solchen, die eine angemessene Bandbreite oder Datenrate haben. Was den dazu notwendigen physischen Kommunikationskanal betrifft, findet man aus verschiedenen Gründen einen sehr spezialisierten und historisch über Jahrzehnte gewachsenen Lebensraum vor, der Operational Technology (OT) genannt wird. Zumeist findet man Zwei- und Vierdraht-Techniken mit Strom- und Spannungs-Signalübertragung, zum Beispiel mit 4–20 mA. Kommunikationsstandards wie eingangs erwähnt, wie Ethernet oder W-Lan sind absolut die Seltenheit. Dieses wird für die sogenannte Informationstechnik (Information Technology, IT) eingesetzt und ist aus Sicherheitsgründen heute komplett von der OT getrennt.
Auch wenn es der OT nicht gefällt, wachsen die beiden Welten IT und OT aber stetig weiter zusammen, da die IT bereits viele funktionierende und preislich attraktive Lösungen bereithält. Die vermeintliche Sicherheit, Verfügbarkeit und Echtzeitfähigkeit der klassischen OT, aber auch ihre Komplexität müssen im Zuge der Digitalen Transformation nun sorgfältig abgewogen werden.
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.
Recently, AI procedures have also been successfully used for NMR data evaluation. In order to overcome the typical limitation of too small data sets from process developments, a new method was tested, which allows a physically motivated multiplication of the available reference data together with context information in order to obtain a sufficiently large data set for the training of machine learning algorithms.
In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
New developments in spectroscopic techniques for process control are, in general, driven by shortcomings of existing technology, for example, when sensitivity, selectivity, robustness, and so forth do not meet the demands. The perfect process analytical method would be based on a robust and easy to handle customized technique operating in real time, come without any need for calibration, that is, be an absolute method, have a professional support, and be compliant to increasing regulatory requirements. However, there are at least trends toward such an all-in-one device suitable for every purpose.
Small, low-field NMR systems equipped with permanent magnet technology have been developed and allow for quantitative analysis as on-line instruments in a production environment. Quantitative high-resolution on-line NMR spectroscopy contributes to process understanding in pilot plant and research environments.
Laser spectroscopy is a promising field in process analysis owing to its sensitivity and selectivity. Laser-induced breakdown spectroscopy LIBS is a promising field for direct in situ analysis and remote sensing. Applications of quantum-cascade lasers for process analytical applications are a promising technique. Techniques such as cavity ring-down spectroscopy (CRDS), tunable diode laser absorption spectroscopy (TDLAS), and photothermal techniques are briefly introduced.
Recent developments of new detectors have improved X-ray fluorescence analysis (XRF) for qualitative and quantitative on-line evaluation of the elementary composition of liquid or solid samples, regardless of whether compact or bulk material.
The chapter also introduces miscellaneous techniques such as ion mobility spectroscopy (IMS), microwave and dielectric spectroscopy, terahertz spectroscopy, ultrasonic acoustic spectroscopy, and other methods.
Ohne die vielfältigen Messmethoden der Prozessanalysentechnik (PAT) sind viele moderne Anlagen der verfahrenstechnischen Industrie heute nicht mehr wirtschaftlich oder sicher zu betreiben. Dementsprechend erfährt die sich mittlerweile immer mehr als selbstständig etablierende Branche Prozessanalysentechnik einen großen Zuwachs und eine spannende Dynamik. Sie ermöglicht eine Produktion in der geforderten Produktqualität unter optimaler Ausnutzung von Rohstoffen, Anlagen und Energie.
Mit den Technologie-Roadmaps „Prozesssensoren 2005–2015“ [1] (2006) und „Prozesssensoren 2015+“ [2] und [3] (2009) wurden Grundlagen für alle Unternehmen der Prozessindustrie geschaffen, um zielgerichtet auf Kundenbedürfnisse der Prozessindustrie zugeschnittene Produktentwicklungen, technologische Weiterentwicklungen und Forschungsprojekte zum Erfolg zu bringen. Die Roadmap „Prozesssensoren 2015+“ fand große Akzeptanz aufgrund der soliden Betrachtung der Prozesse und der daraus abgeleiteten Thesen. Diese Aussagen haben in vollem Umfang weiterhin Gültigkeit. Im Rückblick auf die damals formulierten Entwicklungsziele wurden viele dieser Ziele im prognostizierten Zeithorizont auf den Weg gebracht und teilweise bereits umgesetzt. In dieser Technologie-Roadmap werden einige Beispiele dazu aufgezeigt.
Due to recent advances in technical developments of NMR instruments such as acquisition electronics and probe design, detection limits of components in liquid mixtures were improved into the lower ppm range (approx. 5–10 ppm amount of substance). This showed that modern NMR equipment is also suitable for the observation of hydrocarbon samples in the expanded fluid phase or gas phase. Since Quantitative NMR spectroscopy (qNMR) is a direct ratio method of analysis without the need of calibration it was used to determine impurities in appropriate liquid and liquefied hydrocarbon isomers up to C6, which are used for preparation of primary gas standards, e.g., natural gas or exhaust gas standards. At the same time it is possible to yield structural information with a minimum of sample preparation. Thus, cross contaminations between different isomers of the observed hydrocarbons and their (NMR-active) impurities can be identified and quantified.
In general, most quantitative organic chemical measurements rely on the availability of highly purified compounds to act as calibration standards. The traceability and providence of these standards is an essential component of any measurement uncertainty budget and provides the final link of the result to the units of measurement, ideally the SI. The more recent increase in the use of qNMR for the direct assessment of chemical purity however can potentially improve the traceability and reduce the uncertainty of the measured chemical purity at a reduced cost and with less material. For example the method has beneficially been used by National Measurement institutes for recent CCQM comparisons including the CCQM–K55 series of purity studies.
Traditional ‘indirect’ methods of purity analysis require that all impurities are identified and quantified, leading to a minimum of 4 individual analytical methods (organic impurities, water, solvents, inorganic residue). These multiple technique approaches measure an array of different chemical impurities normally present in purified organic chemical compounds. As many analytical methodologies have compound-specific response factors, the accuracy and traceability of the purity assessment is dependent on the availability of reference materials of the impurities being available.
qNMR provides the most universally applicable form of direct purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. The development of CRMs addressing qNMR specific measurement issues will give analysts compounds ideally suited for the analytical method and also provide full characterisation of qNMR related parameters to enable more realistic uncertainty budgets. These materials will give users the tools to exploit qNMR more easily and enable them to speed up analytical method development and reduce the time and financial burden of multiple analytical testing.
Der Vortrag stellt die aktuellen Forschungsschwerpunkte zum Thema Prozessanalytik an der Bundesanstalt für Materialforschung und -prüfung (BAM) vor und nennt aktuelle Entwicklungsfelder mit dem Ziel gemeinsamer F&E-Projekte. Zunächst wird die Prozessindustrie und ihre Wertschöpfungskette vorgestellt. Daraus ergibt sich eine Motivation für Prozessanalytik. Zwischen der Prozessanalytik in der Pharmazeutische Industrie und der Chemischen Industrie bzw. Verfahrenstechnik gibt es Unterschiede, die herausgearbeitet werden. Der Vortrag schließt mit Technologiewünschen und Technologievisionen und nennt Konkrete Beispiele für Visionen für PAT, insbesondere im Kontext des Zukunftsprojekts „Industrie 4.0“
Quantitative NMR Spectroscopy (qNMR) provides the most universally applicable form of direct purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. Broadly accepted validation methods of qNMR spectroscopy will give users the tools to exploit qNMR more easily and enable them to speed up analytical method development and reduce the time and financial burden.
The first initiative towards a worldwide agreement goes back to a panel discussion at PANIC 2014 (Practical Applications of NMR in Industry Conference) in Chicago. Since that, the Validation Workshop takes place following the PANIC Conference each year, last in 2017 with a turnout of over 50 people. The group aims at identifying a network of NMR people concerned with validation that can ultimately assist each other through the validation process, harmonize the terminology and a standard approach for NMR validations and position the guidelines produced by consensus of the NMR community so that accreditation agencies can use this process.
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 Aufbruch von der aktuellen Automation zum smarten Sensor hat bereits begonnen. Automatisierungstechnik und Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. 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 Sensoren untereinander zu kommen, muss mindestens ein einheitliches Protokoll her, das alle Sensoren 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.
Eine Topologie für smarte Sensoren, das Zusammenwirken mit daten- und modellbasierte Steuerungen bis hin zur Softsensorik sowie weitere Anforderungen an Sensoren sind jedoch heute noch nicht angemessen beschrieben. Wir müssen jetzt schnell die Weichen für eine smarte und sichere Kommunikationsarchitektur stellen, um zu einer störungsfreien Kommunikation aller Sensoren auf Basis eines einheitlichen Protokolls zu kommen, welches alle Sensoren ausgeben und verstehen.
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 und 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.
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.
Homogen katalysierte Reaktionsschritte sind ein wichtiges Werkzeug in der chemischen Industrie. Durch die milden Reaktionsbedingungen hinsichtlich Temperatur und Druck bei gleichzeitig hoher Selektivität bieten diese die Möglichkeit energieeffizienter und ressourcenschonender Produktionsschritte. Eine der wichtigsten industriellen Anwendungen bildet die Hydroformylierung. Hier besteht das Katalysatorsystem meist aus Übergangsmetallkomplexen, vorwiegend Kobalt und Rhodium, die zur Steuerung der Selektivität und Löslichkeit mit mehrzähnigen Liganden koordiniert sind. Diese Komplexe liegen für eine effiziente Katalysator-rückführung in wässriger Lösung vor, was jedoch die Anwendbarkeit auf kurzkettige Edukte mit hinreichender Wasserlöslichkeit beschränkt.
Ein möglicher Lösungsansatz für die Verwendung langkettiger Alkene ist die Umsetzung der Reaktion in einer Mikroemulsion. Durch die gesteigerte Phasen-grenzfläche besteht ein effektiver Kontakt von Katalysator und Reaktanden bei gleichzeitiger Möglichkeit der Produktseparation durch Phasentrennung, während der Katalysator dem Reaktionsschritt zurückgeführt wird und das Verfahren damit wirtschaftlich macht.
Am Beispiel der Reaktion von 1-Dodecen zu Tridecanal wird der Einsatz von Online-NMR- und -Raman-Spektroskopie für die Prozessanalytik (sowie Applikation von komplexen Regelungskonzepten) innerhalb eines mizellaren Systems demonstriert. Ein speziell konzipierter Laboraufbau ermöglicht die Durchführung von Experimenten unter Prozessbedingungen für die in Mikroemulsionen äußerst anspruchsvolle Entwicklung und Kalibrierung von multivariaten Modellen für die Raman-Spektroskopie. Diese konnten anschließend im Rahmen einer mehrtägigen Betriebs-studie einer Miniplant am realen technischen System erprobt werden.
Quantitative NMR Spectroscopy (qNMR) provides the most universally applicable form of direct purity determination without need for reference materials of impurities or the calculation of response factors for all samples exhibiting suitable NMR properties. Broadly accepted validation methods of qNMR spectroscopy gives users tools to exploit qNMR more easily and enables rapid analytical method development and reduce time and financial burdens.
The first initiative towards a worldwide agreement goes back to a panel discussion at PANIC 2014 (Practical Applications of NMR in Industry Conference) in Chicago. Since that time, the Validation Workshop takes place each year following the PANIC Conference, last in 2017 with a turnout of over 65 people. The group aims to identifying a network of NMR people concerned with validation that can ultimately assist each other through the validation process, harmonize the terminology and a standard approach for NMR validations and position the guidelines produced by consensus of the NMR community so that accreditation agencies can use this process.
The talk briefly summarises the outcome of the former PANIC Validation Workshops (2015, 2016, and 2017) as well as the recent satellite meetings including the qNMR meeting held at Spectral Service in Cologne, Germany (June 2016), a validation workshop at SMASH (La Jolla, USA, September 2016), the qNMR Summit with USP in Rockville, USA (October 2016), the qNMR Summit at BAM in Berlin, Germany (March 2017), and the qNMR Minisymposium at SMASH in Baveno, Italy (September 2017).
Upcoming activities will be a qNMR Summit held by JP and JEOL in Tokyo, Japan (January 29th-30th, 2018) and a qNMR Summit at the University of Würzburg, Germany (planned for October 2018). The next PANIC takes place March 4th-8th, 2018 in La Jolla (San Diego), CA, USA.
Further Information can be found under:
http://www.validnmr.com
In general, most quantitative organic chemical measurements rely on the availability of highly purified compounds to act as calibration standards. The traceability and providence of these standards is an essential component of any measurement uncertainty budget and provides the final link of the result to the units of measurement, ideally the SI. The more recent increase in the use of qNMR for the direct assessment of chemical purity however can potentially improve the traceability and reduce the uncertainty of the measured chemical purity at a reduced cost and with less material. For example, the method has beneficially been used by National Metrology Institutes for comparisons including comparisons on CCQM (Consultative Committee for Amount of Substance: Metrology in Chemistry and Biology, www.bipm.org). First comparisons started 1998 with CCQM-P3 (Organics in solution) or CCQM-P35 (2002, EtOH in solution), were underpinned by a broad range of polarity and molecular size (CCQM–K55 series of purity studies including Valine, Aldrin, or Folic acid) and were continued with the recent pilot studies CCQM-P150 (2014, purity of Dimethyl sulfone) or CCQM-P150b (2017, purity of Pyributicarb).
Traditional ‘indirect’ methods of purity analysis require that all impurities are identified and quantified, leading to a minimum of four individual analytical methods (organic impurities, water, solvents, inorganic residue). These multiple technique approaches measure an array of different chemical impurities normally present in purified organic chemical compounds. As many analytical methodologies have compound-specific response factors, the accuracy and traceability of the purity assessment is dependent on the availability of reference materials of the impurities being available.
qNMR provides the most universally applicable form of direct purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. The development of CRMs addressing qNMR specific measurement issues will give analysts compounds ideally suited for the analytical method and also provide full characterisation of qNMR related parameters to enable more realistic uncertainty budgets. These materials will give users the tools to exploit qNMR more easily and enable them to speed up analytical method development and reduce the time and financial burden of multiple analytical testing.
Due to recent advances in technical developments of NMR instruments such as acquisition electronics and probe design, detection limits of components in liquid mixtures were improved into the lower ppm range (approx. 5–10 ppm amount of substance) qNMR studies increasingly attract broader interest.
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 environments 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.
Validation report on NMR
(2017)
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).
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.
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.
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.
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.
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).
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.
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.
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.
Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals
(2019)
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.
Current and future requirements to industrial analytical infrastructure—part 2: smart sensors
(2020)
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.
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).
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.
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.
Calibration-Free Chemical Process and Quality Control Units as Enablers for Modular Production
(2021)
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.