Abstract Brass and brass alloys are widely employed industrial
materials because of their excellent characteristics such as
high corrosion resistance, non-magnetism, and good machinability.
Surface quality plays a very important role in the
performance of milled products, as good surface quality can
significantly improve fatigue strength, corrosion resistance, or
creep life. Surface roughness (Ra) is one of the most important
factors for evaluating surface quality during the finishing
process. The quality of surface affects the functional characteristics
of the workpiece, including fatigue, corrosion, fracture
resistance, and surface friction. Furthermore, surface
roughness is among the most critical constraints in cutting
parameter selection in manufacturing process planning. In this
paper, the adaptive neuro-fuzzy inference system (ANFIS)
was used to predict the surface roughness in computer numerical