## 3 Results and Discussion
IR monitoring signals showed a contrary effect (0.7 V vs. 0.4 V, for 5 and 10 mm). In this case, the measured infrared signal was related to temperature [25], which decreased in the thicker plate as a consequence of heat conduction phenomena, according to the literature [27]. Comparing the cases where different assist gases were used, the presence of oxygen caused an exothermic reaction with the metal producing more heat, and thus, a higher IR signal (0.4 V vs. 1.3 V). Furthermore, the resulting oxidation during the cutting process damaged the cut edge, which the literature associates with an increase in the emissivity coefficient. In the VIS signal, on the contrary, the nitrogen cutting process served as a shielding gas, stopping the burning process and allowing the laser to vaporize the material, increasing the plume formation (0.6 V vs. 0.4 V). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{6}{c}{**Monitoring Signal Mean Levels (V)**} \\ \hline \multirow{2}{*}{**Case**} & \multicolumn{3}{c}{**VIS Gain**} & \multicolumn{3}{c}{**IR Gain**} \\ \cline{2-6}  & **1** & **2** & **3** & **1** & **2** \\ \hline Al, N\({}_{2}\), 5 mm, 5 kW & 0.1 & 0.1 & 0.15 & 0.1 & 0.7 \\ Al, N\({}_{2}\), 10 mm, 5 kW & 0.1 & 0.1 & 0.6 & 0.1 & 0.4 \\ Al, O\({}_{2}\), 10 mm, 5 kW & 0.1 & 0.1 & 0.4 & 0.25 & 1.3 \\ SS, N\({}_{2}\), 10 mm, 5 kW & 0.1 & 0.25 & 1.5 & 3 & 10 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Signal monitoring values for different visible spectrum (VIS) and IR gains at ideal process parameters (Table 1). For 5 mm-thick aluminum, gain 4 was also tested with the same results as gain 3. Figure 2: Monitoring signal mean levels for ideal laser cutting process parameters: (**a**) Visible spectrum and gain 3; (**b**) Infrared spectrum and gain 2. During the experiments, to determine the direct relationship between the parameter values and the monitoring signal response, relevant cutting process parameters such as focal position, laser power, gas pressure, and velocity were modified, testing different values that maintained a good cut quality or that displayed different grades of damage over the lateral cut wall piece. Specifically, three types of defects were detected: (i) regular quality defects in the lateral faces of the cutting pieces associated to regular peaks in the monitored signal, (ii) increase in the monitored mean level due to continuous bad lateral quality, and (iii) signal saturation as a consequence of a cutting loss. Furthermore, different parameters of the machine were registered (speed, real positions, accelerations, temperatures, etc.) to relate them to the cutting process parameters and the quality of the results. Thus, it was possible to determine the exact position of the defects detected by the photodiode in the physical pieces. The investigation was conducted testing the VIS and IR spectrum, with the aim of checking the capability of the photodiode system to detect failures in different scenarios. Figures 3-6 show the results obtained in the tests carried out for each case, using the optimum gain for process observation. As indicated in Figure 3 for stainless steel, no variations in monitoring signals were found, while the good quality was conserved, confirming the independence between the process parameters and the registered signal values for the studied cases. As the same behavior was observed in both spectra, Figures 3-6 only show results in the IR spectrum, but generally, the VIS signal  
Figure 4 displays the tests corresponding to the 10 mm-thick aluminum plate and nitrogen as the assist gas. The focal position of \(-2.8\) mm generated bad lateral quality in the beginning of the test resulting in an increase in the monitoring signal, decreasing later as good quality was achieved. The test of \(-3.2\) mm of focal position and the test with 4700 W show a general increase in the mean level of the monitored signal as a consequence of bad lateral quality during all the cut.