Research on optimization of surface roughness of aspherical aluminum during Single-Point Diamond Turning using BBK model and PSO algorithm
Abstract
The paper presents the results of optimizing the surface quality of aspheric aluminum during Single Point Diamond Turning (SPDT) based on the Box-Behnken Design (BBD) experimental method. The experimental dataset consists of 15 experiments established from the BBK model, supported by the ANOVA module in the specialized software DESIGN EXPERT. The objective function for roughness was established, resulting in a second-order multivariable regression equation that defines the roughness of the aspheric surface based on the data obtained after conducting all experiments. The objective function is formed based on the relationship between the roughness of the aspheric surface and the cutting parameters: spindle speed (n - RPM); feed rate (F - mm/min); and depth of cut (ap - mm). The modeling results, with a reliability of R2 =0.9536, show a high correlation between the model data and the experimental values. By using the Particle Swarm Optimization (PSO) algorithm, the optimal surface roughness value achieved is 0.8 nm, obtained under the machining conditions of n = 2000 RPM, F = 8 mm/min, and ap = 4.2 µm. This study is significant for enhancing the optical surface quality in ultra-precision machining and provides a reliable foundation for building experimental models to optimize and accurately assess the machining process.
