Author:
Eisen Kristina,Eifert Tobias,Herwig Christoph,Maiwald Michael
Abstract
AbstractThe 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).
Funder
Bundesanstalt für Materialforschung und -prüfung (BAM)
Publisher
Springer Science and Business Media LLC
Subject
Biochemistry,Analytical Chemistry
Reference12 articles.
1. Bakeev KA. Process analytical technology. Oxford: Wiley-Blackwell; 2005. Org Process Res. 19: 3–62.
2. Maiwald M. Prozessanalytik als Instrument des Informationsmanagements in der Chemischen und Pharmazeutischen Industrie. Chem Ing Technik. 2010;82:383–90.
3. DIN SPEC 91345:2016-04 Reference Architecture Model Industrie 4.0 (RAMI4.0). – https://www.beuth.de/en/technical-rule/din-spec-91345/250940128. Accessed 23.12.2019. The Reference Architectural Model RAMI 4.0 and the Industrie 4.0 Component. 2015. ZVEI. – https://www.zvei.org/en/subjects/industrie-4-0/the-reference-architectural-model-rami-40-and-the-industrie-40-component/. Accessed 23.12.2019.
4. White Paper: Module-Based Production in the Process Industry – Effects on Automation in the “Industrie 4.0” Environment. 2015. White Paper. ZVEI - Zentralverband Elektrotechnik- und Elektronikindustrie e. V. https://www.zvei.org/en/press-media/publications/white-paper-module-based-production-in-the-process-industry/. Accessed 23.12.2019.
5. Hoffmeister, M. 2015. Industrie 4.0: Die Industrie 4.0-Komponente. Flyer des ZVEI - Zentralverband Elektrotechnik- und Elektronikindustrie e. V. zur Hannovermesse 2015
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