Digital Twin Readiness of Mechanical Coffee Dryers: A Systematic Review

Thermal drying is a critical phase in coffee processing, significantly influencing energy consumption, moisture uniformity, storage stability, and sensory quality. Despite the superior throughput of mechanical dryers over open-sun drying, these systems often operate with limited observability and manual control. This systematic review evaluates the readiness of mechanical coffee drying for Digital Twin (DT) integration. A comprehensive search across Scopus, Web of Science, IEEE Xplore, and ScienceDirect identified 22,859 records. Following multi-stage screening, 58 studies were retained for qualitative synthesis, categorized into a primary coffee-drying corpus and a secondary transferable corpus of methods from related food-processing applications. Findings indicate that while DT-enabling components, such as CFD models, drying-kinetics models, IoT monitoring, and non-destructive sensing, are established, they remain fragmented. No fully implemented and operationally validated DT for mechanical coffee drying was identified. Based on the evidence, a hybrid reduced-order physics-based model integrated with constrained supervisory control represents the most defensible near-term architecture. Future research should prioritize standardized datasets, uncertainty-aware soft sensors, and field validation across diverse dryer topologies and operating conditions.