Industrial Fed-Batch Fermentation Monitoring

Gregersen, Lars; Jørgensen, Sten Bay; Andersen, Maria Yolanda

doi:10.1016/s1474-6670(17)43138-7

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…The history and trends of PLS/CCA techniques, especially PLS, follow the same lines as the development of PCA. Works have been developed for applications concerning batch processes [168][169][170][171][172][173][174], dynamics [169,[175][176][177][178][179][180][181][182][183][184][185][186][187][188][189][190][191][192], nonlinearity [119,185,[193][194][195][196][197][198], multimodality [199][200][201][202], multiple time scales [119,[203][204][205], multiple units and/or stages [125,170,193,[206][207][208]…”

Section: Pls/cca Assumptionmentioning

confidence: 99%

Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey

Melo,

Câmara,

Pinto

2024

Processes

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This paper presents a comprehensive review of the historical development, the current state of the art, and prospects of data-driven approaches for industrial process monitoring. The subject covers a vast and diverse range of works, which are compiled and critically evaluated based on the different perspectives they provide. Data-driven modeling techniques are surveyed and categorized into two main groups: multivariate statistics and machine learning. Representative models, namely principal component analysis, partial least squares and artificial neural networks, are detailed in a didactic manner. Topics not typically covered by other reviews, such as process data exploration and treatment, software and benchmarks availability, and real-world industrial implementations, are thoroughly analyzed. Finally, future research perspectives are discussed, covering aspects related to system performance, the significance and usefulness of the approaches, and the development environment. This work aims to be a reference for practitioners and researchers navigating the extensive literature on data-driven industrial process monitoring.

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Section: Pls/cca Assumptionmentioning

confidence: 99%

Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey

Melo,

Câmara,

Pinto

2024

Processes

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“…Since then, other researchers have adopted the approach and applied it to a variety of processes. For example, Gallagher et al (1996) applied the technique to monitor nuclear waste storage vessels and Gregersen et al (1997) investigated the detection of faults in a fed-batch fermentation process.…”

Section: Multiway Multivariate Statistical Process Controlmentioning

confidence: 99%

Process monitoring of an industrial fed‐batch fermentation

Lennox

Montague

Hiden

et al. 2001

Biotech & Bioengineering

149

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Market demand places great emphasis in industry on product quality. Consequently, process monitoring and control have become important aspects of systems engineering. In this article we detail the results of a 2-year study focusing on the development of a condition monitoring system for a fed-batch fermentation system operated by Biochemie Gmbh in Austria. We also demonstrate the suitability and limitations of current state of the art technologies in this field and suggest novel modifications and configurations to improve their suitability for application to a fed-batch fermentation system.

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