@inproceedings{ca56f66542bf4abfbcdcfa05cae1ccdd,
title = "Hybrid bioprocess model towards the development of a digital twin for an industrial fermentation process",
abstract = "This study presents a bioprocess hybrid model towards the usage in a digital twin framework for an industrial fermentation process involving filamentous fungi. The hybrid model consists of a Light Gradient Boost Machine Model (LGBM) that predicts a viscosity value based on seven online features enabling an accurate prediction of a dynamic profile of for the volumetric oxygen mass transfer coefficient (𝐾𝐿𝑎). The features with the greatest impact on the viscosity predictions are accumulated ammonia flow, accumulated carbon evolution rate (CER) and accumulated air flow. The results highlight the importance of investing in online data, e.g. online viscosity, and digital technologies such as AI and data-driven modelling, to improve prediction accuracy.",
keywords = "Hybrid model, Light gradient boost machine model, Online viscosity model, Oxygen mass transfer coefficient",
author = "Marc Lemperle and Pedram Ramin and Julian Kager and Benny Cassells and Stuart Stocks and Gernaey, \{Krist V.\}",
year = "2025",
language = "English",
series = "Systems \& Control Transactions",
publisher = "EUROSIS",
pages = "199--200",
editor = "\{Van Impe\}, \{ Jan F. M.\} and L{\'e}onard, \{Gr{\'e}goire \} and \{S. Bhonsale\}, Satyajeet and \{E. Polanska\}, \{Monika \} and Logist, \{Filip \}",
booktitle = "ESCAPE 35: 35th European Symposium on Computer Aided Process Engineering 2025",
note = "35th European Symposium on Computer Aided Process Engineering (ESCAPE 35) ; Conference date: 06-07-2025 Through 09-07-2025",
}