Rearch On The Influence Law Of Brass Micro-milling Process Parameters To Surface Roughness And Prediction Model

With the development of science and technology, the requirements of micro parts and components with micro complex3D morphological features are ever increasing. Therefore, the micro-milling technology, which can process complex3D micro parts and components (the feature size is in microns to millimeter) with a wide choice of materials, has become the focus and hotspot of research. Micro-milling surface roughness is one of the important performance indexes in micro-milling processing, and comprehensively reflects the influence of cutting parameters and system variables to micro-milling processing. The difference between micro-milling and conventional milling is that the surface roughness of micro-milling is hard to control, because the phenomenon of scale effect caused by the minimum cutting thickness existing in micro-milling processing. Furthermore, the surface roughness of micro-milling is easier to be affected in the actual process by the deformation or wear of tools and microstructure such as the heterogeneity of materials. Thus, researching on the influence law of different process parameters to micro-milling surface roughness and establishing a high-precision prediction model of micro-milling surface roughness have important significance to accurately predict and control the surface roughness of micro-milling.Based on the micro-milling CNC machine, some micro-milling process experiments were carried out in this paper. The influence law of different process parameters to the surface roughness of micro-milling brass are researched, and two prediction models of micro-milling surface roughness about brass material and four cutting parameters (extended length of micro-milling tool, spindle speed, feed per tooth, depth of cut in the axial direction) are established by both RSM (Response surface method) and SVMR (Support Vector Machine Regression) methods. Then, some machining experiments are executed to contradistinctively verify prediction accuracy of the both models. This paper mainly includes the following:First of all, the hardware and software system of the pre-built CNC micro-milling machine are perfected so as to lay a foundation for the below micro-milling process experiments in this paper. On the hardware, the electric control system is designed, also the handwheel control function is realized successfully. As for software, the G-code compiling for micro-milling machine NC system based on PMAC is designed and realized, so the micro parts with complex geometry features can be automatically processed on the machine. Then, in order to verify the processing performance of the machine and the feasibility of typical metal parts by micro-milling, some micro-milling process experiments are carried out on the materials such as brass, aluminum, and polyimide covered with copper material.Secondly, considering the micro-milling machine and tools, the orthogonal experiments about the main cutting parameters is designed to analyse the influence law of different process parameters to the surface roughness of brass micro-milling, which can lay a foundation for establishing the prediction model of micro-milling surface roughness in the next chapter.Finally, two prediction models about brass material and four cutting parameters(extended length of micro-milling tool, spindle speed, feed per tooth, depth of cut in the axial direction) are established by both RSM and SVMR methods, and then some machining experiments are executed to contradistinctively verify prediction accuracy of the models, so as to seek a high-precision prediction model about specific process parameters.The research of this paper, as an aspect of the research on the micro-milling surface roughness, has great guiding significance to the research on the influence law of different process parameters to the surface roughness and prediction model.