Dunlan Song

During magnetorheological microjet polishing (MMJP) of hard and brittle surface materials such as glass, non-uniform material removal often occurs. To address this issue, this paper proposes a collaborative control framework integrating dynamic path planning and dwell time optimization. First, an 8-direction priority search combined with the A* algorithm is employed to generate full-coverage toolpaths, while dynamically adjusting node attributes (coordinates, status, removal targets) to minimize dead zones. The dwell time is optimized through deconvolution and non-negative least squares (NNLS), where the geometric characteristics of the toolpath directly influence the convolution process of the removal function. Numerical simulations demonstrate that, compared to conventional methods, the synergy between path planning and dwell time control reduces the toolpath distance by 16.29% and improves surface roughness uniformity by 28.22%. Experimental validation under identical process parameters shows a 32.7% greater reduction in surface roughness. This method exhibits significant advantages in enhancing polishing uniformity, reducing machining errors, and shortening toolpath distances, providing novel theoretical and practical support for the application of magnetorheological microjet polishing in ultra-precision machining of hard surface materials.

The magnetorheological jet polishing (MJP) technique, as a revolutionary flexible contact polishing approach, is exceptionally suitable for the smooth and ultra-smooth machining of functional surfaces with tiny or microstructures due to the following essential advantages. Machine tool accuracy is not required and there is nearly no tool wear in addition to high polishing efficiency, minimal surface damage, great surface shape adaptation, superior material removal process selectivity, and so on. This work examines the machining mechanism, the development of machining devices, and the optimization of the process parameters in MJP. This review also covers the MJP technique’s existing limitations and opportunities.

To analyze the effect of particle shape on deformational behavior in the cutting simulation process for metal matrix composites (MMCs), two 2D mesoscopic-based finite element (FE) models reinforced with randomly distributed circular and irregular polygonal particles were developed. Different material properties (metal matrix phase, particle reinforced phase) and the properties of the particle–matrix interface were comprehensively considered in the proposed FE model. Systematic cutting experiments were conducted to compare the differences between two modeling approaches with respect to particle fracture, chip formation, cutting force and surface integrity. The results show that the irregular polygonal particle model is closer to the microstructure of MMCs, and is better able to reflect the deformation behavior of particles. The simulation model with irregular polygonal particles is even able to capture more details of the impact caused by particles, reflecting variations in the cutting force in the actual cutting process. The initiation and propagation of microcracks is mainly determined on the basis of particle geometry and further affects chip formation. Both models are able to correctly reflect surface defects, but the irregular polygonal particle model provides a more comprehensive prediction for the subsurface damage of MMCs.