Research on Structural Optimization and Process Parameter Response Surface Optimization of Vacuum Low-Temperature Fish Meal Dryer

To address the industry pain points of domestic traditional fish meal processing equipment, such as low protein retention, low drying efficiency, and poor operational reliability, this study focuses on high-moisture, heat-sensitive cod meal as the test material to investigate the structural improvement and synergistic optimization of process parameters for vacuum low-temperature fish meal dryers. The conventional uniform-pitch heating coil was optimized into a three-section differentiated structure, with a wear-resistant protective structure additionally incorporated to fundamentally resolve issues including insufficient heat transfer at the feed end, coking at the discharge end, and coil wear-induced leakage. Verification via COMSOL Multiphysics simulation revealed that the axial temperature gradient of the optimized equipment decreased from 8.6 °C/m to 6.2 °C/m, while the thermal fatigue life of the coil was extended from 2–3 years to over 10 years. A three-factor, three-level response surface methodology (RSM) was employed to design the experiments, with the heating temperature, vacuum degree, and drying time as independent variables and the fish meal protein content as the response variable. A total of 17 experimental runs were constructed, including 12 factorial points and 5 central points; each run was replicated three times in parallel, and data were reported as mean values. Analysis of variance (ANOVA) demonstrated that the regression model was highly statistically significant (p < 0.0001), with a coefficient of variation (CV) of 0.2464% and a coefficient of determination (R2) of 0.9944, indicating excellent fitting accuracy. The determined optimal process parameters were as follows: a drying temperature of 65 °C, vacuum degree of 0.08 MPa, and drying time of 75 min. Compared with the traditional process, the optimized process shortened the drying cycle by 37.5%, reduced unit energy consumption by 29.2%, and increased the fish meal protein content by 6.6%. This research provides a reliable technical solution for the localized processing of high-end fish meal.