Abstract
Abstract In this paper, Response Surface Methodology (RSM) was utilized as a robust and convenient predictive tool to establish the correlation between process parameters in in-situ laser-assisted machining and the surface roughness of single-crystal silicon. Based on the optimally designed diamond tool, a novel temperature field analysis method and RSM. The contribution rate of each process parameter on surface roughness was laser power > rotation speed > cutting depth > feed rate. The optimal process parameter combination is: rotation speed as 1001r/min, feed rate as 4.9μm/r, cutting depth as 7.55μm, and laser power as 28.81 W. Experimental validation of these optimal parameters compared surface roughness values obtained experimentally with those predicted. The surface roughness model showed a maximum relative error of 5.2%, with an average error of 4.8% across three experimental sets. These errors are within acceptable limits, indicating an alignment between predicted and experimental results.
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