Retrospective quality by design r(QbD) for lactose production using historical process data and design of experiments

Quality by Design (QbD) is a popular formal approach for designing, upscaling and optimizing industrial production facilities towards guaranteed quality. To avoid the many costly experiments required for QbD, historical production data may be exploited for optimization instead in what is known as a...

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Veröffentlicht in:Computers in industry 2022-10, Vol.141, p.103696, Article 103696
Hauptverfasser: Galvis, Leonardo, Offermans, Tim, Bertinetto, Carlo G., Carnoli, Andrea, Karamujić, Emina, Li, Weiwei, Szymańska, Ewa, Buydens, Lutgarde M.C., Jansen, Jeroen J.
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Sprache:eng
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Zusammenfassung:Quality by Design (QbD) is a popular formal approach for designing, upscaling and optimizing industrial production facilities towards guaranteed quality. To avoid the many costly experiments required for QbD, historical production data may be exploited for optimization instead in what is known as a retrospective QbD (rQbD) study. Current rQbD literature does limitedly discuss data-driven identification of Critical Process Parameters (CPPs) to optimize limited process knowledge availability, and does not cover situations where technical operation limits have not yet been fully explored and/or where parallel equipment (lines) are used. This work presents a new rQbD strategy that addresses these challenges by balancing knowledge that can be obtained from statistical analysis of historical data, together with process experts with a carefully designed set of plant-scale experiments within current operational limits. This novel strategy is demonstrated on a long-running industrial lactose production facility. By digitally and experimentally exploring historical operation variability, we found new operational regimes for this production that may lead to up to 7% product quality improvement, reduced energy consumption and increased process understanding. Although optimizing a specific process by necessity requires a process-specific approach, the way in which we systematically optimize the current process with Hybrid AI (combining available knowledge with new insights from historical data) shows that approaches that are currently used in prospective process upscaling may be modified to be invaluable for optimization of full-scale processes with a long operational history. •A new comprehensive strategy for retrospective quality by design for industry has been developed.•This strategy optimally fuses knowledge of historical data, experiments and experts.•The strategy is demonstrated on a full-scale lactose crystallization plant.•For this plant, new operation regimes that may lead to up to 7% product quality increase were identified.
ISSN:0166-3615
1872-6194
DOI:10.1016/j.compind.2022.103696