## 4 Analysis of Results  
With the integration of new technologies for scaling up to an intelligent MPS, we proceed with the validation of the system, through experimental tests of batch order requests, i.e., the performance of the MES will be identified when integrated with the plant processes, unexpected failures of the internet service and the plant response to the execution of production orders. At start-up, the MES executes different instructions in parallel such as connectivity with the cloud, ensuring a bidirectional information flow with the cloud services, preparing the management of SQL queries in the local database, setting up bidirectional communication with the ESP32 master and executing an AI model for the detection and segmentation of parts captured in images at station (D). This system start-up situation was considered to have a slow loading time due to the concurrent execution of these processes on a specific processing space, a situation necessary to update the stock of products in the plant in real time. On the other hand, the performance of the reconnection of the MES with the web server in case of a failure in the quality of service (QoS) of the internet provider was evaluated. To simulate this situation, the internet service was interrupted, and through the cloud connectivity response, the resilience results presented in Table 3 were obtained. In addition, the speed at which data can be sent and received between the web server and the MES, located at the edge of the plant, is detailed. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Work Center** & **Business** & **Functional** & **Information** & **Communication** & **Integration** & **Asset** \\ \hline \multirow{4}{*}{\begin{tabular}{c} **Work** \\ **Center** \\ \end{tabular} } & \multirow{4}{*}{\begin{tabular}{c} Limited use \\ due to \\ production \\ focus \\ \end{tabular} } & Process & Production & Communication & Technology & Physical \\  & & & & line & Integration: & stations and \\  & & & indications & between work & Integration of & assets \\  & & & and data & centers and & control and & interacting \\  & & & & managed by & control systems & production & within the \\  & & & center & & systems & work center \\ \hline \multirow{4}{*}{\begin{tabular}{c} **Enterprise** \\ **Enterprise** \\ \end{tabular} } & Limited use & Process & Performance & Design of & Node-RED and & \begin{tabular}{c} Documentation \\ and \\ management \\ \end{tabular} \\  & & & & & communication & for data and \\  & & level, including & management & infrastructure to & process & physical and \\  & & quality and & across the & support & integration & virtual assets \\  & & & enterprise via & production & across the & at the \\  & & & the MES & & enterprise & enterprise \\ \hline \multirow{4}{*}{\
\begin{tabular}{c} **Connected World** \\ **Connected World** \\ \end{tabular} } & Limited use & Collaborative & Storage and & Global & Technology &
\begin{tabular}{c} Virtual assets \\ that extend \\ \end{tabular} \\  & & & & & Integration: & beyond the \\  & & part of a network & & coordination for & \\  & & of partners and & & backed up & production & \\  & & & & process & systems and \\  & & & & partners & and cloud \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Cont. The message exchange connection process between MES/CLOUD-CLOUD/MES, managed from Node-Network, records times for the stock update of 1.3 s and for the download of order requests of 0.35 s. On the other hand, during the asynchronous serial communication between MES/ESP Master-ESP Master/MES, times for manufacturing orders sent to station (A) are recorded as 0.26 s and for the storage of local data received from station (D) as 0.24 s.  
With the integration of the new technologies into the MPS 500 system, an optimized production line has been designed that, when receiving a mini-batch order, divides the task into two parallel processes. The first process handles product dispatch, starting at station (D) and ending at station (E), with an estimated time of 45 s per part.