Abstract
To achieve precise feeding, this study coupled a Discrete Element Method (DEM)-based virtual test platform with the Response Surface Method (RSM) to quantitatively evaluate and optimize the effects of traveling speed (X₁), scraper rotation speed (X₂), and conveyor belt speed (X₃) on unit feeding amount (Y₁) and feeding uniformity (Y₂). A simplified core model of the feeding device was established in EDEM, and the cohesive characteristics of Total Mixed Ration (TMR) were characterized using the Hertz–Mindlin with JKR Cohesion contact model. A three-factor, three-level Box–Behnken experimental design was employed to fit quadratic regression models for Y₁ and Y₂. The results indicated that both models were statistically significant (P < 0.0001). The significant influencing factors for Y₁ were ranked as X₁ > X₂ > X₃, while those for Y₂ were ranked as X₂ > X₃ > X₁. Based on the analysis of interaction effects among parameters and multi-objective desirability optimization (targeting Y₁ = 10–12 kg·m⁻¹ and maximizing Y₂), the optimal combination was determined as X₁ = 3.05 km·h⁻¹, X₂ = 84.9 r·min⁻¹, and X₃ = 326.5 r·min⁻¹. After rounding for engineering application, X₁ = 3 km·h⁻¹, X₂ = 85 r·min⁻¹, and X₃ = 330 r·min⁻¹ yielded verification results of Y₁ = 11.49 kg·m⁻¹ and Y₂ = 91.54%, with prediction deviations below 5%. Within the studied geometric and parameter ranges, the material flow remained continuous and stable, without persistent arching or blockage. Therefore, the analysis primarily focused on uniformity and throughput. This study provides executable operational parameters and a transferable parameter design approach applicable to cohesive feed systems