Zengbin Yin

Study on high-speed cutting parameters optimization of AlMn1Cu based on neural network and genetic algorithm

In this article, the cutting parameters optimization method for aluminum alloy AlMn1Cu in high-speed milling was studied in order to properly select the high-speed cutting parameters. First, a back propagation neural network model for predicting surface roughness of AlMn1Cu was proposed. The prediction model can improve the prediction accuracy and well work out the higher-order nonlinear relationship between surface roughness and cutting parameters. Second, considering the constraints of technical requirements on surface roughness, a mathematical model for optimizing cutting parameters based on the Bayesian neural network prediction model of surface roughness was established so as to obtain the maximum machining efficiency. The genetic algorithm adopting the homogeneous design to initialize population as well as steady-state reproduction without duplicates was also presented. The application indicates that the algorithm can effectively avoid precocity, strengthen global optimization, and increase the calculation efficiency. Finally, a case was presented on the application of the proposed cutting parameters optimization algorithm to optimize the cutting parameters.

Surface topography and roughness of high-speed milled AlMn1Cu

The aluminum alloy AlMn1Cu has been broadly applied for functional parts production because of its good properties. But few researches about the machining mechanism and the surface roughness were reported. The high-speed milling experiments are carried out in order to improve the machining quality and reveal the machining mechanism. The typical topography features of machined surface are observed by scan electron microscope(SEM). The results show that the milled surface topography is mainly characterized by the plastic shearing deformation surface and material piling zone. The material flows plastically along the end cutting edge of the flat-end milling tool and meanwhile is extruded by the end cutting edge, resulting in that materials partly adhere to the machined surface and form the material piling zone. As the depth of cut and the feed per tooth increase, the plastic flow of materials is strengthened and the machined surface becomes rougher. However, as the cutting speed increases, the plastic flow of materials is weakened and the milled surface becomes smoother. The cutting parameters (e.g. cutting speed, feed per tooth and depth of cut) influencing the surface roughness are analyzed. It can be concluded that the roughness of the machined surface formed by the end cutting edge is less than that by the cylindrical cutting edge when a cylindrical flat-end mill tool is used for milling. The proposed research provides the typical topography features of machined surface of the anti-rust aluminum alloy AlMn1Cu in high speed milling.