This paper investigates precision error compensation technology for complex surface machining on CNC milling machines. With the rapid development of high-end manufacturing

the accuracy requirements for free-form surfaces in aerospace

mold

and precision instrument industries continue to rise. However

machining errors caused by tool deformation

thermal displacement

and servo lag remain major obstacles to achieving ultra-precision performance. To address these challenges

this study proposes a comprehensive error compensation model that integrates geometric calibration

thermal error modeling

and intelligent adaptive control. The method applies multi-source data fusion and machine learning to predict and compensate dynamic errors during machining. Experimental results show that the proposed approach effectively improves surface accuracy and stability

reducing form deviation by over 35%. The research provides theoretical and practical support for advancing intelligent and high-precision CNC milling of complex surfaces.