<p>Ice-Assisted Drilling technology has emerged as an effective solution for achieving high-quality, precision drilling of thin-walled components, leveraging its inherent advantages of environmental sustainability, exceptional dimensional accuracy, and superior surface integrity. However, multi-objective optimization research for ice-assisted drilling of thin-walled components remains unexplored, with no systematic studies reported in the literature. This study performs a multi-objective optimization of ice-assisted drilling for Ti-6Al-4V alloy thin-walled components, targeting surface roughness, flatness, parallelism, roundness, and cylindricity as key geometric quality indicators. Firstly, an orthogonal experimental design was implemented, with freezing temperature, feed rate, and spindle speed as control factors, followed by execution of ice-assisted drilling experimental. Secondly, the effects of cutting parameters and freezing temperature on the surface roughness, flatness, parallelism, roundness and cylindricity of thin-walled parts after drilling were systematically studied. Finally, based on the grey correlation analysis method, the multi-objective optimization of process parameters is carried out, and the optimal process combination is determined, and its effectiveness is verified by experiments. The results show that the global optimal parameter combination is <i>n</i> = 600 r/min, <i>f</i> = 120 mm/min, <i>T</i> = − 5&#xa0;°C; the influence weight of process parameters is ranked as ice temperature &gt; spindle speed &gt; feed speed. This study delivers a critical theoretical foundation and actionable technical guidance for optimizing high-precision thin-walled component drilling processes.</p>