The growing demand for functional foods has increased the need for efficiency and reliability in the logistics of the food sector. However, the low service level in order deliveries continues to represent a critical barrier for manufacturing companies, especially those still operating with minimally automated logistics processes. This issue is mainly attributed to inaccurate demand planning, inventory control errors, and limited product traceability, which result in significant delays and economic losses. To address this challenge, this study introduces an integrated logistics model that combines Industry 4.0 tools through a practical and adaptable approach: Demand Driven MRP (DDMRP) powered by ARIMA predictive models and RFID technology integrated with Kanban systems. The main novelty of this model lies in its synergistic and automated design, enabling the system to dynamically respond to demand fluctuations and correct operational deviations through real-time feedback. Specifically, the implementation of these tools enables automatic feedback and real-time system adaptation in response to demand changes. The results show a 13.72% improvement in the service level, enabling the company to reach the industry standard of 97%. Furthermore, the proposed methodology proves to be scalable and adaptable to various food industry environments. In conclusion, this approach promotes the adoption of smarter, more sustainable, and customer-oriented logistics practices.