A Review of Artificial Intelligence Applications for Biorefineries and Bioprocessing: From Data-Driven Processes to Optimization Strategies and Real-Time Control
Lucian Blaga University of Sibiu · Universidad Nacional de Educación a Distancia · +1 more institution
Abstract
This paper reviews the integration of artificial intelligence (AI) and machine learning in biorefineries and bioprocessing, with applications in biocatalysis, enzyme optimization, real-time monitoring, and quality assurance. AI contributes to predictive modeling and allows the precise forecasting of process outcomes, resource management, and energy utilization. AI models, including supervised, unsupervised, and reinforcement learning, support improvements in important bioprocess stages, such as fermentation, purification, and microbial biosynthesis. Digital twins and soft-sensing technologies enable real-time control and increase operational precision in complex bioprocess environments. Hybrid modeling…
Citation impact
- FWCI
- 48.38
- Percentile
- 100%
- References
- 64
Authors
5Topics & keywords
- Bioprocess
- Computer science
- Biochemical engineering
- Process engineering
- Control (management)
- Artificial intelligence
- Engineering
- Chemical engineering