## Part Functionality as Effected by Surface Topography  
### Machined Surface Topography Characteristic  
The surface topography of any manufacturing process is a critical index. It is mainly affected by geometric properties of the machining system for milling process. Choosing suitable cutting parameters  
Figure 1: The effect of surface integrity on part functionality. for given tools, workpiece materials, and machine tools is an important step to get reasonable surface topography. Because the two-dimensional parameters cannot properly represent the surface features of milling, more and more attention is being paid to three-dimensional parameters today. Considerable research has been performed to get suitable surface topography. [PERSON] et al. [13] provided in-depth characterization and analysis of the three-dimensional topography of feed direction and cross-feed direction in the hard milling process of AISI H13 steel (AISI is an abbreviation of American Iron and Steel Institute), as shown in the Figure 2. The results show that better surface morphology can be obtained by using higher cutting speed, lower feed speed, and lower cutting depth. [PERSON] et al. [14] studied the surface morphology and surface roughness in the milling process of AlMn1 Cu. Due to the high ductility of the AlMn1 Cu material, the material flows plastically along the side-cutting edge and meanwhile is extruded by the side-cutting edge to cause the material to accumulate on the machined surface. With the increase of cutting depth and feed per tooth, the plastic flow of the material along the cutting edge is strengthened, resulting in increased surface roughness. However, with the increase of cutting speed, the plastic flow of the material is weakened along the secondary cutting edge, resulting in that the surface roughness value decreases. [PERSON] et al. [15] found that high cutting speed, low feed rate, and low cutting depth can be used to obtain ideal surface quality in the semifinishing and finishing process of AISI H13 steel. Some scholars carried out the research of prediction of surface topography for milling process. As established by experimental tests, the actual roughness values obtained usually deviates from theoretical ones. There are several reasons accounting for this, such as runout of the milling cutter tooth tips, rounding of the cutting edge, and irregularities of cutting edge [16]. In order to design a machining process for blades in turbine engines without prior experiment, [PERSON] et al. [17] developed a model to predict the surface topography. The effect of stochastic topography on the flow losses was investigated also in his research. The machined surface was studied by combining the dynamic morphology with the random topography based on empirical data. The results show that the random morphology has a great influence on the flow loss and therefore cannot be ignored. [PERSON] et al. [18] proposed a milling topography simulation model considering tool wear. The experimental results of cutting under plane and cylindrical surfaces are in good agreement with the model prediction, which proves the correctness of the model. [PERSON] et al. [19] established a numerical model to predict the surface topography of milling process based on the contact relationship between tool and workpiece. [PERSON] et al. presented an analytical model that considered the effects of tool geometry, cutting conditions, and plastic flow measurements to predict surface topography [20]. [PERSON] et al. established a surface topography prediction model considering tool vibration [21]. [PERSON] et al. [22] established an analysis model for the surface topography of five-axis milling process considering cutting parameters, number of cutting edges, and cutter runout. Figure 2: Surface topography of milling surface [13]. (**a**) Surface texture zones in milling and (**b**) surface topography by milling process. The cutting trajectory is another factor that should not be neglected in the prediction model of surface topography.