## 2 Literary Review and State of the Art
### MES (Manufacturing Execution System)  
A manufacturing execution system (MES) is a comprehensive software solution that manages, monitors and optimizes production operations in real time within an industrial plant. This type of system enables efficient workflow management, synchronizing the different production stations and ensuring the quality and consistency of the final product. In the context of Industry 4.0, MES becomes a central component for integrating plant automation with advanced data analysis and decision-making services, facilitating the connection between the plant and external systems such as the cloud. In addition, the incorporation of technologies such as FC and the allocation of specific resources within the MES allow critical and distributed tasks to be handled, improving responsiveness and operational efficiency [47]. On the other hand, and with the objective of providing an integral solution for the management of industrial processes in an Industry 4.0 environment, it is highlighted that a hybrid SOA-MES integrates the flexibility and modularity of a service-oriented architecture (SOA) with the operational capacity and real-time control of an MES. This hybrid approach allows plant operations to be connected and coordinated with advanced cloud services such as data analytics, artificial intelligence and critical information storage. The SOA facilitates communication and interoperability between different distributed services, while the MES ensures that plant operations are managed efficiently and without disruption. This type of architecture is especially useful in industrial  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref.** & **Proposed Topics** & **Main Advantages** & **Challenges and Limitations** & **Added Value with the Implemented Study** \\ \hline
[33] & MES in Industry 4.0 & Synchronization of stations and real-time management & Limited integration with external systems & Expands interoperability with IoT and FC \\ \hline
[34] & Hybrid SOA-MES & Real-time connection with advanced services (AI, data) & Implementation complexity in SMEs & Flexible architecture facilitates adaptation \\ \hline
[35] & Fog Computing (FC) in MES & Reduced latency, fast real-time response & Requires robust infrastructure & FC and MES operating on multiple levels simplify infrastructure and distribute loads \\ \hline
[36] & RAMI 4.0 with IoT and Blockchain & Data security and transparency & High integration costs & Connectivity benefits at a lower cost \\ \hline
[37] & Digital Twins in Automotive Plant & Flexibility and advanced simulation & Requires extensive database & Local and cloud data handling reduces complexity without using DT \\ \hline
[38] & ISA-95 in Industry 4.0 Environment & Efficient task management and scalability & Limited interoperability with new technologies & Improves interoperability with FC and IoT \\ \hline
[40] & OPC UA in Industrial Communication & Standardization of protocols & Requires robust and constant network & Node-RED enables flexibility without constant network dependency \\ \hline
[41] & Fog Computing for Manufacturing & Network resilience and continuous processing & Requires trained personnel & Eases I4.0 operations for SMEs \\ \hline
[42] & SCADA and Big Data Integration & Real-time data monitoring and analysis & Complexity in SCADA data management & Use of local databases reduces complexity \\ \hline
[43] & HMI with ERP in Production Line & Data digitization and traceability & Limited configuration flexibility & MES facilitates customizable configurations \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of technological approaches in Industry 4.0: advantages and limitations.  
environments where the combination of local control and cloud services allows for greater flexibility, scalability and resilience in the face of changing conditions and increasing demands [48].