## 2 Experimental Research
### Main Experiment and Analysis of Obtained Results
As shown in Figure 5, there was a trend of increase in the value of coating thickness along with the increase of current and voltage for the coating applied on carbon steel. Figure 6 shows the trend of increasing coating thickness values with increasing voltage for all current values when the coating is applied to galvanized steel. More precisely, coating thickness remains the same if the current and voltage are 31.7157 and 88.2834 uA. When the voltage is increased, the coating thickness increases as well. As presented by Figure 7,  
Figure 6: Response surface for the regression model of the dependence of coating thickness for galvanized steel. Figure 7: Response surface for the regression model of the dependence of coating thickness for aluminum. As seen in Figure 8, residuals (i.e., internally studentized residuals--transformed or scaled residuals) were distributed normally, since there were no significant deviations from the line. Figure 9 shows that errors, i.e., residuals, did not correlate (there was neither negative nor positive correlation) with certain values and that they did not exceed the diagram boundaries in values of \(\pm 3\). The points in the diagram are colored according to the response (coating thickness). Figure 10 presents both the actually measured values and the values predicted by the model. Figure 10: Actual and predicted value—coating thickness. Figure 9: Residuals—predicted values—coating thickness. Based on the above-presented research results, it is possible to optimize the input parameters (current and voltage) in order to obtain the target value of an output (thickness of applied coating) for each of the tested materials. Table 8 gives an overview of the limitations set for each of the input parameters, as well as the target value of the coating thickness. Table 9 contains the optimal values of input parameters for achieving target coating thickness on carbon steel, galvanized steel and aluminum. The optimal solution, i.e., optimal values, of the input parameters (current and voltage) for the achievement of the target thickness of the coating on carbon steel is presented in Figure 11, on galvanized steel in Figure 12 and on aluminum in Figure 13.  
The analysis of the research results obtained within this experiment confirmed that voltage and current have a great influence on the thickness of the coating. This hypothesis  
Figure 12: Optimal values of input parameters for the achievement of target thickness of coating on galvanized steel. Figure 13: Optimal values of input parameters for the achievement of target coating thickness on aluminum. was already confirmed in the preliminary experiment, within which only combinations of limited values were examined. The more comprehensive effect of their interaction was examined in the main experiment. The conducted research thus provides insight into how important the implementation of a scientific approach is in all segments of production processes. Namely, the individual effect of certain process parameters that are defined here as input variables is very easy to verify; however, what is also extremely important is the interaction of individual parameters and their effects. By using software for experimental planning and statistical data processing, the interaction effect of all input variables of the planned experiment on the output variable (coating thickness) was clearly demonstrated. As previously mentioned, in preliminary research using classical methods and a simple experimental plan, it is only possible to observe that certain changes can result in varying combinations of parameters. However, with more detailed analysis and processing, it is possible to arrive at mathematical models with which it is possible to assess cause-and-effect relationships; it is also possible to perform additional analyses of the collected data in order to define the optimal values of individual parameters that will result in the desired values and characteristics of the individual observed property.