Modern day monitoring and control challenges outlined on an industrial-scale benchmark fermentation process
| Autor: | Barry Lennox, Carlos A. Duran-Villalobos, Suzanne S. Farid, Stephen Goldrick, David Lovett, Karolis Jankauskas |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Process (engineering) 020209 energy General Chemical Engineering Big data 02 engineering and technology Fault detection and isolation Modelling Resource (project management) 020401 chemical engineering Penicillin fermentation Control 0202 electrical engineering electronic engineering information engineering Process Analytic Technology (PAT) 0204 chemical engineering Process engineering Quality by Design (QbD) business.industry Industrial scale Monitoring and control Computer Science Applications Biopharmaceutical Raman spectroscopy Benchmark (computing) business Fault detection |
| Zdroj: | Goldrick, S, Duran-villalobos, C A, Jankauskas, K, Lovett, D, Farid, S S & Lennox, B 2019, ' Modern day monitoring and control challenges outlined on an industrial-scale benchmark fermentation process ', COMPUTERS & CHEMICAL ENGINEERING . https://doi.org/10.1016/j.compchemeng.2019.05.037 |
| Popis: | This paper outlines real-world control challenges faced by modern-day biopharmaceutical facilities through the extension of a previously developed industrial-scale penicillin fermentation simulation (IndPenSim). The extensions include the addition of a simulated Raman spectroscopy device for the purpose of developing, evaluating and implementation of advanced and innovative control solutions applicable to biotechnology facilities. IndPenSim can be operated in fixed or operator controlled mode and generates all the available on-line, off-line and Raman spectra for each batch. The capabilities of IndPenSim were initially demonstrated through the implementation of a QbD methodology utilising the three stages of the PAT framework. Furthermore, IndPenSim evaluated a fault detection algorithm to detect process faults occurring on different batches recorded throughout a yearly campaign. The simulator and all data presented here are available to download at www.industrialpenicillinsimulation.com and acts as a benchmark for researchers to analyse, improve and optimise the current control strategy implemented on this facility. Additionally, a highly valuable data resource containing 100 batches with all available process and Raman spectroscopy measurements is freely available to download. This data is highly suitable for the development of big data analytics, machine learning (ML) or artificial intelligence (AI) algorithms applicable to the biopharmaceutical industry. |
| Databáze: | OpenAIRE |
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