RT Journal Article
T1 How could Artificial Intelligence be used to increase the potential of biorefineries in the near future? A review
A1 Arias Calvo, Ana
A1 Feijoo Costa, Gumersindo
A1 Moreira Vilar, María Teresa
K1 Artificial Intelligence
K1 Biorefineries
K1 Sustainability
K1 Eco-design
K1 Sustainable management
AB Innovation in digitalization and low-carbon technologies are leading the way for the production sector. In the context of the bioeconomy, a path is opening up for the integration of bio-based processes into the value chain as alternative production schemes to fossil fuel-based production models, although process modeling and optimization is needed as this approach is at an early stage of design and development. The large number of variables in the biorefinery cascade scheme presents the inherent difficulty of the optimization strategy, considering conditions that allow for higher productivity and revenues in parallel with lower environmental burdens. The implementation of artificial intelligence (AI) through techniques such as machine learning and predictive modeling could be considered as an efficient tool for process optimization. Such techniques require large amounts of historical data to identify effects, synergies and clusters of parameters; detect production anomalies; develop models for predictive, prescriptive or root cause analysis; and provide autonomous control.In this sense, this critical review report aims to provide an overview of available reports that have considered AI for the evaluation of biorefinery production models, identifying its potentialities to enable better production strategies under the principles of sustainability and circular economy. This review aims to be useful for the development of further research on the implementation of digitalization of biorefinery processes. This work aims to identify the forefront innovations in the development of bio-based processes that meet efficiency and sustainability criteria in order to provide information of interest to policy makers, stakeholders and industry professionals
PB Elsevier
SN 2352-1864
YR 2023
FD 2023-11-01
LK http://hdl.handle.net/10347/31226
UL http://hdl.handle.net/10347/31226
LA eng
NO Environmental Technology & Innovation 32 (2023) 103277
NO A. Arias, G. Feijoo and MT Moreira authors belong to the Galician Competitive Research Group (GRC, Spain ED431C 2017/29) and to the Cross-disciplinary Research in Environmental Technologies (CRETUS Research Center, Spain , ED431E 2018/01)
DS Minerva
RD 24 abr 2026