Thin-walled components are widely used in precision instruments and defence equipment, and mirror milling is an advanced machining method for such structures. To overcome the limitations of conventional rigid supports, this study proposes an adaptive air-jet support technology. Numerical simulations were conducted to analyse the effects of nozzle geometry on air-jet force, and the optimal design was obtained. An adaptive air-jet support device and control system were then developed. Based on full-factorial experiments, a neural network model for predicting axial milling force was established to determine control parameters under different cutting conditions. This enables real-time adaptive control of the air jet. Experimental results show that the proposed method effectively enhance the stability and improves surface quality, providing a non-contact solution for enhancing mirror milling performance.
Yuan et al. (Wed,) studied this question.