## 3 Results and Discussion  
As shown in Figure 8, the data points captured using the laser scanner were complete and had better quality in terms of lesser noise, insignificant gaps or holes, consistent boundary, etc. On the contrary, the data points acquired by using white light scanner possessed inconsistent edges or borders, greater noise, numerous gaps or holes, etc., as shown in Figure 9.  
The primary defects observed in the data acquired by using white light scanner were missing data (e.g., small holes, gaps, etc. ), erratic borders or edges, higher noise, etc., as shown in Figure 10. These  
Figure 8: Data points obtained with laser scanner—(**a**) best model; (**b**) worst model. Figure 7: Measurement of accuracy using a 3D comparison (**a**) best fit of scanned and CAD models (**b**) 3D comparison results. gaps or irregular edges complicate the subsequent steps such as surface reconstruction process and diminish the efficiency of RE process. In addition, big holes were observed that might have resulted from unrecognized target points in which the scanner assumed the targets as holes. The RMS value of deviations, scanning time, and triangle numbers at different combinations of scanning parameters can be seen in Table 3. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & \multicolumn{5}{c}{**Viu Scan**} \\ \hline
**Run No.** & **Laser Power** & **Shutter** & **Resolution** & **Deviation** & **Triangle Numbers** & **Scanning** \\  & **(\%)** & **Speed (ms)** & **(mm)** & **(mm)** & **(Triangle)** & **Time (min)** \\ \hline \(1\) & 100 & 3 & 1.5 & 0.271 & 542,682 & 16.53 \\ \(2\) & 50 & 9 & 1.5 & 0.296 & 531,517 & 14.77 \\ \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) \\ \(26\) & 75 & 9 & 3 & 0.182 & 130,259 & 9.82 \\ \(27\) & 50 & 3 & 3 & 0.11 & 127,331 & 10.03 \\ \hline \hline \multicolumn{7}{c}{**Go Scan**} \\ \hline
**Run No.** & & \multicolumn{2}{c}{**Shutter**} & **Resolution** & **Deviation** & **Triangle Numbers** & **Scanning** \\  & & **Speed (ms)** & **(mm)** & **(mm)** & **(Triangle)** & **Time (min)** \\ \hline \(1\) & & 0.5 & 2 & 0.341 & 4,963,900 & 3.7 \\ \(2\) & - & 8 & 1.5 & 0.221 & 568,445 & 1.683 \\ \(\cdots\) & & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) & \(\cdots\) \\ \(17\) & & 4 & 0.5 & 0.217 & 5,232,900 & 4.55 \\ \(18\) & & 4 & 1.5 & 0.181 & 573,965 & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: A sample data for Laser Scanner (ViuScan) and White Light Scanner (GoScan). Figure 10: Defects in the data points of the white light scanner—(**a**) missing data; (**b**) edge defects. Figure 9: Data points obtained using white light scanner—(**a**) best model; (**b**) worst model. To confirm the normality of the data sets, a normality test of data points for each response was carried out. Subsequently, to analyze the results, ANOVA and main effect plots were studied. The normality assumption for accuracy shown in Figure 11 depicts that the data points were normal and could successfully be used for ANOVA. Similarly, normality tests for the other response (scanning time) of the two scanners confirmed their normality for consecutive analyses as shown in Figure 12. Normality test for the number of triangles in laser scan was valid as shown in Figure 13a, whereas the normality test for the number of triangles in white light scan was not valid as shown in Figure 13b. Therefore, the Log data transformation was conducted and the normality assumption was tested again as shown in Figure 13c. It is clear that the normality assumption was valid (refer Figure 13c). The measurement units for residuals are same as that of the response. For example, the measurement unit for the residual of scanning time is in minutes. An ANOVA test with 95% confidence was performed to determine the significance of the parameters, as well as the interaction between them.