# Intelligent Monitoring and Compensation between EDM and ECM
## 3 Case Results
### Edm  
The EDM process uses a pulsed current to melt the electrode extremely close to the area where the workpiece is. It is often used to manufacture parts or molds with high complexity or hard materials. For the installation of voltage probes and current hooks on the EDM as presented in Figure 10, the electrical signals of the machine spindle were collected and signal analysis was conducted. EDM requires a long time and has a high discharge frequency (>10 kHz) in Figure 11, and therefore, a large amount of data was collected. Feature calculation and extraction  
Figure 10: EDM Machine and sensing configuration. Figure 9: Comparisons of model predictions with experimental results. from the data are complex. For analyzing EDM process quality, typical steps include data collection, feature calculation, model building, and quality estimation in Figure 12.  
The workpieces processed using ECM were processed through EDM in sequence. The final results are presented in Figure 13, and the three-dimensional measurement results are presented in Table 4. The exit (the sixth level) was observed and is presented in EDM measurement results. Different processing conditions were observed before EDM processing, and further improvement was required. After ECM, the shape was incorrect and had high roughness. Yet, this process saved much time, reducing machining time from hours to minutes. EDM was then used; it is superior for use with nickel-based alloys, which are difficult materials for machining. Figure 11: Current and voltage signals of characteristics of EDM. Figure 13: Comparison before and after processing. As presented in Table 4 and Figure 14, EDM must be connected with different sizes after different processing parameters of ECM. To be closest to the actual processing state, we discussed the export. In data analysis, approximately 20% of the data collected before the end of processing was analyzed, and the results after calculating the characteristics were assessed subsequently. The model for estimating the machining effective area and protocol matching led to enhanced efficiency and path optimization of the ECM process. To estimate one diffuser with 88 polygon shape hole machining, the total working time provided the superior time of 7.3 h to combine ECM and EDM. In comparison, in the traditional process using only EDM, the time consumed is 4.8 days. The discharge performance was indicated with high ASF values, suggesting high machining efficiency. In the observations, the removal area No. 1 > No. 2 > No. 3 > No. 4 > No. 5 was observed in the CMM results. After the calculation of the characteristics using this method, the ASF was observed to be No. 1 > No. 2 > No. 3 > No. 4 > No. 5. The larger contact areas and spark frequencies are presented in Figure 15.  
In the CMM results, the obtained removal area was No. 1 > No. 2 > No. 3 > No. 4 > No. 5. After calculating the characteristics of this method, No. 5 was observed in the AIDT > No. 4 > No. 3 > No. 2 > No. 1. Thus, the contact area was larger, and the spark delay time was shorter. High AIDT values indicate that the capabilities of slag removal and motion control require improvement, as presented in Figure 16. Subsequently, 20% of the data before the completion of processing was captured for use as the subsequent model data. In data analysis, a staged change was observed. With the difference of the contact area, features were identified and predicted, and the training of the neural network was conducted in this manner.