TY - JOUR A1 - Maiwald, Michael T1 - The internet of things in the lab and in process - The digital transformation challenges for the laboratory 4.0 T1 - Das Internet of Things in Labor und Prozess - Herausforderungen des digitalen Wandels für das Labor 4.0 N2 - It is a fact that much of the time spent on analytical laboratory instrumentation these days goes into system maintenance. Digital transformation could give us more time again for creativity and our actual laboratory work – if we shape it the right way. N2 - Fakt ist: Einen Großteil der Zeit, der an analytischen Laborgeräten verbracht wird, nimmt heute die Systempflege in Anspruch. Der digitale Wandel kann uns endlich wieder mehr Zeit für Kreativität und die eigentliche Laborarbeit geben – wenn wir ihn richtig gestalten. KW - Lab of the Future KW - Digitalisation KW - Automation KW - Data Analysis KW - Instrument Communication KW - Labor der Zukunft KW - Digitale Transformation KW - Automatisierung KW - Gerätekommunikation PY - 2020 IS - 4 SP - 1 EP - 3 PB - Lumitos AG CY - Darmstadt AN - OPUS4-50618 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael T1 - Modular process control with compact NMR spectroscopy – From field integration to automated data analysis N2 - 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 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. T2 - GIDRM Day (Gruppo Italiano Discussione Risonanze Magnetiche) - Data analysis and NMR: from fundamental aspects to health and material applications CY - Online meeting DA - 14.10.2022 KW - Process Control KW - Online NMR Spectroscopy KW - Industry 4.0 KW - Process Analytical Technology KW - Data Analysis KW - Machine-Assisted Workflows PY - 2022 DO - https://doi.org/http://www.gidrm.org/index.php/activities/workshops/2022-workshops/gidrm-day-data-analysis-and-nmr-from-fundamental-aspects-to-health-and-material-applications AN - OPUS4-56002 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -