A Comprehensive Review on AI, Digitalization and Industry 4.0 in Biofuel Production Processes

Author

Bade Venkata Suresh, Yadala Moksha Pradha

Abstract

Rising energy demands and climate concerns have accelerated research into renewable biofuels. However, conventional production processes face challenges like feedstock variability, high energy use, and operational instability. Integrating Artificial Intelligence (AI), digitalization, and Industry 4.0 offers transformative solutions to convert traditional plants into intelligent biorefineries. This comprehensive review critically assesses these advanced technologies—including machine learning, digital twins, IoT, and cyber-physical systems—across major biofuel pathways such as bioethanol, biodiesel, biogas, and algal fuels. It examines their impact on yield prediction, process optimization, energy efficiency, and techno-economic performance. Furthermore, key implementation barriers—such as data limitations, cybersecurity, and industrial-scale validation—are addressed. Finally, an integrated framework connecting AI, digitalization, and Industry 4.0 across the biofuel value chain is proposed to guide future research toward scalable, environmentally sustainable, and intelligent bioenergy systems.

Keywords

Artificial intelligence; Biofuel production; Digitalization; Industry 4.0; Smart biorefineries; Digital twins; Machine learning; Sustainable bioenergy

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References

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