Digital twins are becoming increasingly crucial in Industry 5.0, enabling real-time monitoring, predictive maintenance, and performance optimization. Among all the Industrial Internet of Things (IIoT) platforms available, FIWARE stands out as a programmable open-source platform that facilitates interoperability along with integrated data scaling. This work assesses the implementation of a FIWARE-based digital twin within an actual textile industrial environment, specifically the shift from a conventional data management paradigm to an integrated, data-driven approach in the company Adalberto. Although the architecture is still under development, the proposed design illustrates how real-time monitoring, interoperability, and data-driven decision-making can be improved through the application of FIWARE’s open standards. In contrast with proprietary platforms, FIWARE presents a cost-effective, adaptable option, acknowledging nonetheless that system integration and staff training challenges remain. This paper concludes with best-practice recommendations for introducing open-source digital twins in manufacturing and outlines next steps to test performance and scalability once the new solution is operational.