Effect of Nozzle Parameters and Spindle Speed on the Oil Mist Penetration Mechanism in MQL High-Speed Milling of a GH4169 Alloy

Minimum quantity lubrication (MQL) is a promising green technology for high-speed milling of GH4169. However, the full-chain oil mist penetration mechanism remains unclear, limiting precise parameter regulation. Based on a cross-scale mechanism, this study develops a semi-empirical oil mist penetration efficiency model coupling four key parameters and conducts single-factor and orthogonal high-speed milling experiments to validate the model and analyze the regulation mechanism using milling force and surface roughness. The experimental results show relative deviations below 6%, demonstrating good model validity and robustness. The influence hierarchy is spindle speed > nozzle orientation > nozzle angle > nozzle distance. Spindle speed and nozzle orientation are strongly coupled dominant parameters with a “drive-adaptation” mechanism, while nozzle distance and nozzle angle are weakly coupled, only notable under extreme conditions. The optimal parameters obtained via BP neural network and NSGA-II are nozzle orientation −X, angle 22.43°, distance 14.96 mm, and spindle speed 16,581 rpm. Under this combination, minimum Surface Roughness Ra of 0.17 μm and milling force of 24.27 N are achieved, reducing surface roughness by 85.32% and milling force by 53.52% versus the worst condition and reducing roughness by 28.57% versus the baseline while maintaining milling force within a reasonable range. This study clarifies the physical mechanism of MQL oil mist penetration, extending conventional macroscopic parameter optimization. The proposed cross-scale framework offers theoretical and engineering guidance for MQL parameter design in green precision machining of nickel-based superalloys.