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Modular process control with compact NMR spectroscopy – From field integration to automated data analysis

  • Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparableChemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.zeige mehrzeige weniger

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Autor*innen:Michael MaiwaldORCiD
Koautor*innen:Klas Meyer, Simon Kern, Svetlana Guhl, Martin Bornemann-Pfeiffer, Lukas Wander, Stefan Kowarik, Sascha Liehr, M. Abele, S. Falkenstein
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2022
Organisationseinheit der BAM:1 Analytische Chemie; Referenzmaterialien
1 Analytische Chemie; Referenzmaterialien / 1.4 Prozessanalytik
8 Zerstörungsfreie Prüfung
8 Zerstörungsfreie Prüfung / 8.0 Abteilungsleitung und andere
8 Zerstörungsfreie Prüfung / 8.6 Faseroptische Sensorik
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Freie Schlagwörter:Data Analysis; Industry 4.0; Machine-Assisted Workflows; Online NMR Spectroscopy; Process Analytical Technology; Process Control
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Chemie und Prozesstechnik / Chemische Charakterisierung und Spurenanalytik
Umwelt
Umwelt / Sensorik
Veranstaltung:GIDRM Day (Gruppo Italiano Discussione Risonanze Magnetiche) - Data analysis and NMR: from fundamental aspects to health and material applications
Veranstaltungsort:Online meeting
Beginndatum der Veranstaltung:14.10.2022
Enddatum der Veranstaltung:14.10.2022
DOI:http://www.gidrm.org/index.php/activities/workshops/2022-workshops/gidrm-day-data-analysis-and-nmr-from-fundamental-aspects-to-health-and-material-applications
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:17.10.2022
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
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