## 4 Results and Discussion
Some defective parts were produced on purpose at the tooling development phase in order to stabilize manufacturing processes. Those parts were used to verify the smallest number of points necessary to find an error of the shape, similarly to the previous verification. Table 4 is an evidence of the premise that the number of CMM points needed to verify the part can oscillate around approximately 25 per section on aero-shaped components. In Figure 12 the presented average error tends to be stable for a high number of data points, still aiming to ensure enough accuracy even for a small amount of data. Only one point is needed to find the flaw, but it must be ensured that that specific point can be found during the inspection. A high number of measured points can register the same flaw many times and based on important knots we can limit these significantly. A set of 1000 points contains 256 points outside the tolerance, whilst a set of 50 contains only 11, and a set of 15 contains five. At approximately 25 points, based on knot reduction, it is certain that shapes outside the tolerance can be found. Using just a few points can result in identification of a flaw, but it is by no means certain that all flaw locations will be identified this way or that these will be all the significant flaws for our configuration. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Number of Points**} & **Maximum** & **Average** & \multirow{2}{*}{**Standard**} & **Points Outside the Tolerance Zone** \\  & **Distance** & **Distance** & **Deviation (mm)** & **Toiletance Zone** \\ \hline
1000 & 0.787 & 0.322 & 0.215 & 256 \\
500 & 0.787 & 0.322 & 0.215 & 119 \\
250 & 0.786 & 0.322 & 0.215 & 59 \\
125 & 0.785 & 0.321 & 0.216 & 30 \\
75 & 0.786 & 0.322 & 0.213 & 18 \\
50 & 0.786 & 0.324 & 0.214 & 11 \\
**25** & **0.762** & **0.328** & **0.211** & **6** \\
15 & 0.695 & 0.328 & 0.221 & 5 \\
10 & 0.695 & 0.352 & 0.180 & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Defect part CMM verification. Two areas were found with the shape error shown in Figure 12 on one section. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Turbine**} & **Measured** & **Maximum** & **Average** & \multirow{2}{*}{**Standard**} & **Time of Overall** \\  & **Points** & **Distance** & **Distance** & **Deviation (mm)** & **Inspection (s)** \\ \hline Section 1 & 25 & 0.127 & 0.047 & 0.032 & \\ Section 2 & 25 & 0.102 & 0.055 & 0.025 & \\ Section 3 & 25 & 0.635 & 0.265 & 0.155 & \textless{}300 \\ Trend line & 16 & 0.645 & 0.303 & 0.229 & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Profile measurements of turbine guide vane. The reason why larger groups of points have larger values for error measurement lies simply within the type of measurement. Single points are measured in intervals; a quick sensor movement needs a short time period (about one second) to damp the vibrations. A high number of points (up from 125 in the presented case) is measured by scanning. The speed of the sensor is decreased so as not to induce vibrations, but the speed per single point overall is higher, as the machine is collecting the data continuously, without stopping the probe movement. The scanning method can be less precise, but there is a need for a compromise between the speed and accuracy for this type of inspection and everything rests upon the inspector's experience. Mass inspection can accept small errors, which do not affect the overall inspection quality. Additionally, there is a full overview of the part shape with all the maximum and minimum peaks on the part surface. Tables 3 and 4 results use absolute values for the maximum, average error, and sample standard deviations calculations. Many automation methods were also used for the final path planning, probe adjustments, box of safety (a 3D place where we can use the full speed for CMM without a risk of probe damage), and report generation.