gholamreza Abdi

Artificial intelligence (AI) and machine learning (ML) are revolutionizing the fats and oils processing industry by enhancing operational efficiency, product quality, and sustainability. This chapter examines AI-driven innovations throughout the value chain, from refining and solvent extraction to quality control, predictive maintenance, and regulatory compliance. Techniques such as ML, artificial neural networks, and computer vision are being used to optimize temperature control, solvent selection, adulteration detection, and equipment diagnostics. AI also supports real-time monitoring, waste minimization, and intelligent resource utilization through the use of smart sensors, edge computing, and IoT integration. In supply chain management, AI aids traceability, raw material sourcing, and demand forecasting, although some areas remain underdeveloped. Case studies confirm AI’s practical benefits, while challenges such as data quality issues, infrastructure gaps, and model transparency remain. Future opportunities lie in hybrid modeling, generative AI, and decentralized learning systems. AI's strategic integration promises to accelerate sustainability and productivity across the fats and oils sectors, positioning it for an Industry 4.0 transformation.