Modelling of surface roughness and studying of optimal machining position in side milling

In this work, a theoretical analysis of surface generation numerical model is presented to predict the surface roughness achieved by side milling operations with cylindrical tools. This work is focused on the trajectory of tools with two teeth by the influence of tool errors such as radial runouts, as well as straightness with dynamic effects. A computational system was developed to simulate roughness topography in contour milling with cylindrical tool. Finally, the PSO (particle swarm optimization) algorithm is employed to find the optimal machining position for the best surface roughness. Experimental data is satisfied with the novel protection model for the tooth's trajectory, and the final prediction accuracy is high enough, i.e. that the prediction surface roughness. Low prediction surface roughness error (1.37 similar to 15.04%) and position error (0.95 similar to 1.25 mm) indicate effectiveness of the model built in this work. The novel model may be used to determine the variation in surface roughness.

Automated summary

A theoretical analysis of surface generation numerical model was presented in this work to predict surface roughness in side milling operations with cylindrical tools. The focus was on tool trajectory influenced by tool errors and dynamic effects, with a computational system developed to simulate roughness topography. The PSO algorithm was used to find optimal machining positions for best surface roughness prediction accuracy, with low errors indicating model effectiveness for determining variations in surface roughness.