## 2 Materials and Methods
### Factor Settings after 3D Scanning (Post-Scanning Factors)  
The four factors set after scanning consist of watertightness, simplification, smoothness, and sharpness. Post-scanning factors of 3D scanning are necessarily employed as scanned data are obtained in terms of mesh or point cloud, which strongly needs to be post-processed to reduce data noise and defects with data optimization. When completing the 3D scanning of an object, two immediate options are usually presented in a pop-up window in the EinScan software, i.e., watertight and un-watertight. Watertight and un-watertight are two types of 3D geometric models that imply whether models are closed or unclosed, respectively. As 3D scanned geometric models are virtually complex, watertight models are deemed ready for 3D printing. On the other hand, un-watertight models are not closed and may have open surface patches/holes within the 3D scanned model. Moreover, un-watertight models are not ready for 3D printing and point cloud data need to be further processed (WaterTight_UnWaterlight_WebBlog.pdf, 2022). Watertightness has three levels,  
Figure 4: Colorless scanned object from non-texture scan. Figure 3: Three-dimensional scanned sample geometries with texture scan option. i.e., high detail watertight (HW), medium detail watertight (MW), and low detail watertight (LW). The HW level of watertightness is selected when a fine-texture geometric model is desired, and a smooth-textured geometric model results from MW and LW. Together, the watertight factor has four levels in this study. Namely, HW, MW, and LW represent levels of watertightness, and the fourth level is un-watertight (UW). In addition, four levels of watertightness were set when the texture mode of 3D scanning was used. When the non-texture mode of 3D scanning was employed, only two levels were available: MW and UW. Another post-processing factor is simplification. Simplification simplifies the point cloud data by filling holes using polygon numbers, sizes, and the surface of the data. Its default value is 100%. In this research, three levels of simplification were used: 50%, 60%, and 70%. Therefore, the simplification levels were kept lower than 100% as high percentages of simplification may reduce the actual size of holes which a physical object possess in the details of its features. Smoothness is another post-processing factor. Smoothness imparts a great effect on the scanned data in terms of removing noise from the data. Finally, sharpness (a post-processing factor) provides better clarity of the scanned data and improves the visual appearance of the scanned data up to an optimum scanning quality. Based on the settings of the levels of the factors in Table 1, four modes of 3D scanning (A, B, C, and D) were defined for devising novel frameworks of 3D scanning comprising pre- and post-processing factors. These 3D scanning modes were equally applied to S1 and S2, as shown in Table 2.  
Therefore, a total of twenty-four experiments were conducted for texture scans with sharpness/smoothness and twelve experiments were performed for non-texture scans with sharpness/smoothness. Therefore, the final experiments totaled thirty-six for each sample geometry in this research. Thus, a set of seventy-two experiments were finally conducted for both samples based on a full factorial DOE. For physical metrology, a coordinate measuring machine (CMM) was used to measure the dimensional input parameters of the samples. The 3D scanned samples, as illustrated in Figure 3, were imported to SolidWorks in stl. format to measure the dimensional output \begin{table}
\begin{tabular}{c c} \hline \hline
**Factors** & **Levels** \\ \hline \multicolumn{3}{c}{**Texture with Sharpness/Smoothness**} \\ \hline Watertightness & 4 (LW, MW, HW, and Un-watertight) \\ \hline Simplification & 3 (50\%, 60\%, and 70\%) \\ \hline \multicolumn{3}{c}{**Non-Texture with Sharpness/Smoothness**} \\ \hline Watertightness & 2 (MW and UW) \\ \hline Simplification & 3 (50\%, 60\%, and 70\%) \\ \hline \hline \end{tabular}
\end{table}