JA Calpa, FY Alvarez, JA Echeverry, DF Teuta and NJ Gil
Cenicaña, Colombia; jacalpa@cenicana.org
To address the need to maintain and increase efficiency, as well as to make informed decisions in the sugarcane agro-industrial sector, which are essential for maintaining competitiveness and sustainability, Cenicaña developed DataCane. This tool integrates data from multiple industrial sources, analyzes it, and visualizes key performance indicators in real-time through interactive dashboards. The development of DataCane by Cenicaña involved the secure acquisition of data from different sources, using industrial communication protocols such as Process Control Data Access/Unified Architecture (OPC DA/UA), Message Queuing Telemetry Transport (MQTT), and Application Programming Interface – Representational State Transfer (API-REST), in addition to connections with traditional relational databases, ensuring cybersecurity measures. This enables the processing and analysis of large volumes of data on an accessible and secure platform. Currently, the tool is implemented in four Colombian sugarcane mills, covering processes such as cane preparation and milling, evaporation, steam generation, and quality management. Application has led to significant improvements, such as the transition from static maintenance routines to dynamic ones based on evaporator fouling indicators, which increased operational uptime by 30% and reduced maintenance costs by the same proportion. In addition, data integration has enabled global indicators to be available, making it possible to obtain the factory’s overall balance sheet automatically and in real time. This automation supports decision-making based on up-to-date information. DataCane facilitates the implementation of real-time thermal sucrose loss models, with error margins between 4% and 10%, allowing timely decisions on operational flows and improving sucrose recovery efficiency. In conclusion, DataCane represents a key advancement in the implementation of Industry 4.0 technologies, integrating predictive analytics models, preventive maintenance, and cybersecurity. This initiative drives real-time operational efficiency while ensuring data integrity, establishing a solid foundation for future advancements in process optimization within the sugar industry.