## 4 Results and Discussion
### Measurement Results in Statistical Analysis
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Gear**} & **True** & **Estimator Ratio** & \(\Delta t_{p}\)**, According** & \(T_{true}\) & \(T_{desig}\) & \(\Delta t_{p}\) & **Designed** \\  & **IT Grade** & **in Model X [\%]** & **to DIN 3961 [mm]** & **[mm]** & **[mm]** & **Designed [mm]** & **IT Grade** \\ \hline No 1. Mark 16 & 8 & 81 & \(\pm\)0.014 & 0.028 & 0.023 & \(\pm\)0.012 & 7-8 \\ No 2. Mark 13 & 7 & 80 & \(\pm\)0.013 & 0.026 & 0.021 & \(\pm\)0.011 & 6-7 \\ No 3. Mark 2 & 8 & 65 & \(\pm\)0.019 & 0.038 & 0.025 & \(\pm\)0.013 & 7 \\ No 4. Mark 2 & 8 & 93 & \(\pm\)0.019 & 0.038 & 0.035 & \(\pm\)0.018 & 8 \\ No 5. Mark 3 & 6 & 100 & \(\pm\)0.009 & 0.018 & 0.018 & \(\pm\)0.009 & 6 \\ No 6. Mark 5 & **9** & 53 & \(\pm\)0.017 & 0.034 & 0.018 & \(\pm\)0.009 & 7 \\ No 7. Mark 11 & 7 & 83 & \(\pm\)0.012 & 0.024 & 0.020 & \(\pm\)0.010 & 6 \\ No 8. Mark 6 & 9 & 81 & \(\pm\)0.025 & 0.050 & 0.041 & \(\pm\)0.021 & 8 \\ \hline \multicolumn{2}{c}{Explanations:} & & & \multicolumn{1}{c}{An increase of two IT grades (gear would have to be made more precisely)} & & & \\ \multicolumn{2}{c}{An increase of one IT grade (gear would have to be made more precisely)} & & & \multicolumn{1}{c}{An increase of one IT grade (gear would have to be made more precisely)} & & \\ \multicolumn{2}{c}{The IT grade remains the same} & & & \multicolumn{1}{c}{Remains the same IT grades or increases by one IT grade (more precisely)} & & \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Report on the preliminary analysis of the applicability of Model X. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**IT Grade wg DIN 3961**} & & & & & & & \\ \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**8**} & \multirow{2}{*}{**7**} & \multirow{2}{*}{**8**} & \multirow{2}{*}{**8**} & \multirow{2}{*}{**6**} & \multirow{2}{*}{**9**} & \multirow{2}{*}{**7**} & **Suma** & **Occurrence in** & \\  & & & & & & & & **All Measured** & **Verdict** \\  & \(\downarrow\) & & & & & & **Gears? ** & & \\ \hline \multirow{2}{*}{XI} & \multirow{2}{*}{2} & \multirow{2}{*}{} & \multirow{2}{*}{} & \multirow{2}{*}{} & \multirow{2}{*}{} & 75 & YES & Second \\  & & & & & & & & & best \\  & & & & & & & 110 & YES & Best \\  & & & & & & & 75 & – & – \\  & & & & & & & 70 & – & – \\  & & & & & & & 60 & – & – \\  & & & & & & & 45 & – & – \\  & & & & & & & 25 & – & – \\  & & & & & & & 30 & – & – \\  & & & & & & & 50 & – & – \\  & & & & & & & 0 & – \\  & & & & & & & 0 & – \\  & & & & & & & & 30 & – \\  & & &Each of these mods can be, depending on the type of mod, light, moderate, heavy, micro, normal, macro, initial, or destructive. In addition, there is also a phenomenon called plastic fatigue deformation, which occurs as a result of a certain number of load cycles, at which the mechanical part ceases to be able to further accumulate energy, to such an extent that permanent deformations may occur. Then, it would be possible to adapt such a simulation model to the observed values from measurements on a modern measuring machine. Such a machine generates a graph of the topography of the tooth surface (Figure 14a) and a graph of pitch error (Figure 14b). This is very important because, thanks to this, the designer is able to determine whether there is any connection between the gear wear and the need to shift the data distribution (as mentioned in the previous paragraphs). All factors that should be taken into account in future research on assessing the accuracy of the reverse engineering process (no longer important whether using modern or conventional methods) are presented graphically in Figure 15.  
Figure 14: Two graphs for the Gear No. 2 Mark 13 during measurement on Wenzel WGT 600: (**a**) topography of the tooth surface, (**b**) pitch error and pitch deviations (photos taken from the WGT 600 operating system interface during measurements for the next article, where this will be discussed in more detail).