## 6 Conclusions  
The integration of information technologies (ITs) into operational technologies (OTs) in this study has been fundamental for the transition of a production plant from Industry 3.0 to Industry 4.0, taking the RAMI 4.0 framework as a reference structure. Through this integration, the manufacturing execution system (MES) was able to plan and manage production in an MPS, optimizing waiting times between operations and replenishment time at the storage station by approximately 30%. This parallel manufacturing process enables a 95% reduction in new order start-up times, substantially improving production efficiency and achieving integrated management between the dispatch and manufacturing stages. The implemented hybrid architecture, which combines hierarchical levels in a single control card, facilitates fluid and agile communication between the fog computing (FC) nodes in the plant and between the MES and the cloud, achieving response times of approximately 15 ms and 1.7 s, respectively. This integration not only provides speed but also resilience, allowing the system to operate efficiently even under varying network conditions. However, it is emphasized that the performance of the control unit must be properly managed to avoid thermal overloads, which could slow down the processing speed and affect continuous operation. The FCS node orchestration has proven to be effective, maintaining operating temperatures between 45 \({}^{\circ}\)C and 55 \({}^{\circ}\)C, which ensures efficient energy consumption and reduces the need for additional cooling. In terms of novel contribution, the flexibility of the RAMI 4.0 framework made it possible to integrate and orchestrate key technologies for smart manufacturing, aligning with Industry 4.0 objectives. This solution also presents a scalable and adaptable model for SMEs, enabling a modular and gradual expansion that fits their economic constraints. The implementation of distributed nodes offers SMEs a scalability option aligned with their resources and growth needs. The proposed solution stands out for its flexibility and ability to integrate advanced technologies in a modular manufacturing environment. In addition, by implementing distributed nodes and a hybrid architecture, the system optimizes processing efficiency and allows for gradual expansion according to the company's resources. However, the initial infrastructure and training required to implement these technologies can be a challenge for SMEs facing budget constraints. In addition, while several layers of the RAMI 4.0 framework are covered, areas such as lifecycle management and value stream were not addressed in this implementation, given the focus on real-time production and operation. These aspects can be addressed in future expansions, taking advantage of the flexibility of the RAMI 4.0 framework and the modular structure of the proposed architecture. Overall, this study provides a viable route for the modernization of traditional industries towards an Industry 4.0 model, with an adaptable architecture aligned with the RAMI 4.0 framework. The significant contribution of this research lies in its practical and scalable approach, which offers a solid foundation for the progressive growth of SMEs in the context of digitalization and advanced manufacturing. Conceptualization, W.O. and R.S. ; methodology, W.O. ; software, W.O. and R.S. ; validation, W.O. ; formal analysis, W.O. ; investigation, W.O. and R.S. ; resources, W.O. ; data curation, W.O. ; writing--original draft, W.O. and R.S. ; writing--review & editing, W.O. ; visualization, W.O. ; supervision, R.S. ; review, R.S. ; project administration, W.O. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author. This work was supported by Universidad Politecnica de Madrid (UPM) and Universidad Politecnica Salesiana (UPS).