Study On The High-speed Milling Process For The Weak Rigidity Workpieces Of Anti-rust Aluminum Alloy

The functional parts with anti-rust aluminum alloy are used in radar with the fine characteristic to reflect visible light, heat and electromagnetic waves. In recent years, the research of high-speed machining technology has been widely carried out. But the further research is needed in the the material removal mechanism, tool material, cutting parameters optimization and machining databases, etc. In this paper, by use of high-speed milling technology, the systematic study was carried out on the weak rigidity workpieces processing techniques form the milling force, surface roughness, cutting parameters optimization and machining deformation control. The results have provided technical support to the application of the material, and this research has a broad application value.The theoretical prediction model of three-dimensional milling forces, based on the milling process, was presented. According to the variation of area of shear plane during the single-tooth milling process, the transient milling force was classified. The high-speed milling experiments were carried out, and the workpieces materials is AlMn1Cu. According to the characteristics of cutting forces in the time domain and frequency domain, the change regularity of transient milling force was presented. The cutting mechanism and the typical characteristics of machined surface topography were presented by using scanning electron microscopy.The single-factor, factorial and uniformity test were employed to carry out the high-speed milling experiments for AlMn1Cu. The results of single-factor experiments for AlMn1Cu show the variation of milling force and surface roughness with a certain cutting parameter such as cutting speed, feed-per-tooth and depth of cut. According to the analysis of variance (ANOVA) of factorial experiments, the cutting parameters significantly influencing on the milling forces and the surface roughness were presented. The results show the depth-of-cut is the most statistical significant factor influencing on the milling forces and the surface roughness. The range analysis of factorial experiment indicates the cutting prarameters which the minimum surface roughness is achieved. The predictive mathematic models of milling forces and surface roughness based on the cutting parameters were established by using the partial least-squares regression (PLS), the prediction accuracy of forecasting model is enhanced.The artificial neural network approach is presented for establishing the predictive models of milling forces and surface roughness based on the cutting parameters. In order to achieve the maximum material removal rate, the optimization model of cutting parameters which the constraints are the technical requirements such as the milling forces and surface roughness is built. A genetic algorithm based on simulated annealing is employed to find the optimum cutting parameters leading to maximum material removal rate in the different range of the technical requirements.The finite-element method along with the milling force and toolpath was developed to analyze the machining deformation in peripheral milling of a typical weak rigidity structure such as thin-wall, ultra-thin web and micro-holes/slots. The method was proposed to reduce machining deformation of weak rigidity workpiece from the optimum cutting parameters, tool selection, toolpath arrangement and fixture design.At last, the maching technologies presented in this dissertation have been applied successfully in the practical productions of weak rigidity workpieces, and the testing results of the machined workpieces show that the design technical requirements are met in the machined surface roughness, error of shape and position and dimensional accuracy.