Integrated Modeling, Simulation, and Experimental Optimization of Vibratory Coffee Sorting Performance Using Response Surface Methodology
DOI:
https://doi.org/10.23055/ijietap.2026.33.5.11611Abstract
This study presents an integrated theoretical, simulation, and experimental approach to optimize the performance of a vibratory coffee sorting machine using Response Surface Methodology (RSM). A physics-based model of granular flow and segregation was developed to quantify the influence of inclination angle (α) and vibration frequency (f), and numerical simulations using MATLAB and DEM confirmed nonlinear interactions between both parameters, predicting optimal performance at α = 28.5° and f = 47.5 Hz with a throughput of 3541.3 g/min and sorting accuracy of 98.14%. Empirical validation through a Central Composite Design (CCD) demonstrated significant effects of α and f on system responses (p < 0.001) and produced highly accurate regression models (R² = 98.32% for throughput and R² = 92.52% for accuracy). Multi-response desirability optimization yielded an empirical optimum at α = 29.8° and f = 50 Hz, achieving a throughput of 3667.44 g/min and an accuracy of 98.32%, closely aligning with simulation predictions. The results confirm the robustness of the integrated modeling framework, highlight the inherent trade-off between throughput and segregation efficiency, and provide a practical guideline for improving productivity and quality in vibratory coffee sorting operations.
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