Milling force prediction and optimization of process parameters in micro-milling of glow discharge polymer

Glow discharge polymer (GDP) is widely used for target microshell material as a nominal ablator in inertial confinement nuclear fusion (ICF) applications. The microshells are usually thin (below 0.1 mm) and fragile. Its machinability and machining surface characteristics greatly influence its high-power performance. Milling force prediction and process parameters optimization in micro-milling of GDP are crucial to engrave onto the polymer, forming different required microstructures and meeting the increasing usage requirements. In this paper, a set of single-factor micro-milling experiments of micro-pits on the surface of GDP were designed to evaluate the significance of each process parameter on the milling force and surface roughness (S_a). An orthogonal center composite experiment was adopted to predict micro-milling force and S_a. A set of optimized micro-milling parameters (spindle speed (n), milling depth (a_p), feed rate (f), and tool cantilever length (l)) were obtained. The fitting models of the milling force and S_a were then established using the response surface methods (RSM). The regression coefficients, the accuracy of the models, and the effect of system vibration on surface quality were analyzed. It was found that the proposed model can predict the milling force and S_a accurately. The significance of milling parameters on surface quality is l, f, n, a_p in a decreased order. The optimized milling parameters were obtained as n = 26,000 r/min, a_p = 21.25 μm, and f = 0.02 mm/min. Furthermore, the micro-pit and microgrooves were machined, and S_a was reduced by 68% to 48 nm. The outcomes of this work could provide guidance for milling force prediction and milling parameters optimization in the precision machining of microstructures on GDP material.