## 3 Results  
The developed application was tested to identify the elements of the manufacturing cell, and for this, three tests were carried out with different stages, which we will call stages \"A, B, and C\" (see Figure 5), to identify each case in which the results obtained from the application algorithm are displayed (see Tables 3-5). For the first test, it can be seen that the elements of the stage are enclosed in a box with a label corresponding to the name of the detected element, and the dimension of the inserted image was the original, and in it, all the elements that were expected to be detected in the proposed stage \"A\" were detected (see Figure 5a). The second test was performed  
Figure 5: Testing the stages “A, B, and C”. For each test, an image of the “A, B, and C” area of the manufacturing cell was inserted. Each image turned out different due to the dimension and content displayed of the image selected for each stage. with an image of stage \"B\"; the program recognizes the elements and encloses it in a green outline box with its name as the label. Thus, you can see the test image used for stage \"B\" with the detection of the visible elements (see Figure 5b). In the same way, the third test shows acceptable results in the identification of elements for stage \"C\" (see Figure 5c). However, the developed application manages to correctly identify the element, where it is located with precision and accuracy, displaying it in green outline boxes along with the name of the detected element. Before deploying the application to a production environment, tests were carried out in different stages and conditions of manufacturing zone \"A\" to simulate the possible results when the application is launched in a production environment. Therefore, it will be determined if the elements to be located were as expected, the confidence percentage of the element, and the coordinates at which the element is located in the manufacturing cell space. The corresponding tests for each stage were carried out with the Postman application, which is a tool that serves as a great help for testing applications in development. Testing the application consisted of inserting a test image and stage type into the Postman request to test the Application Programming Interfaces, and in such a way, inspect the results obtained from image processing with the YOLOv8 model that was trained. When submitting the POST (to add the information of the detected elements of the image) type request, a JSON (JavaScript Object Notation) [34] is generated from the Postman [35] terminal with the information found during the prediction of the image of the PCB manufacturing cell. Consequently, the values that the terminal will display will be the confidence or probability that the detected element was as expected, the name of the tagged item, and the coordinates at which the detected item was found. In Figure 6, you can see the test of stage \"A\" validated with the Postman tool of the elements detected in the image. Also, we can observe the elements that were detected that are named after the attribute of the tag. However, we have a confidence probability of no less than 94% that the elements detected are as expected. In addition, we have the coordinates of the element detected in \"x\" and \"y\" of the prediction of the image of stage \"A\". Below are the values of the attributes \"x1\", \"y1\", \"x2\", \"y2\", \"Label\", and \"Trust\", where the coordinates in \"x1\" and \"y1\" show the coordinates of the detected element and \"x2\" and \"y2\" show the dimension  
Figure 6: A stage POST request. of the detected object, which make up the JSON, referring to each element detected in stage \"A\" (see Table 3). In stage B, as inferred from Table 4, calculating the average confidence of the detected elements shows a mean of 0.97, similar to stage A. In stage C, the average confidence of the detected elements was 0.98. This indicates that the results in Table 5 achieved a slightly higher confidence percentage than the two previous stages.