Optimizing Sugar Factory Operations Using Cloud based IoT And Predictive Analytics

Abstract

Manual checks used to monitor the sugar industry are the cause of inefficiencies and unplanned downtimes considering that the sugar industry struggles to curb these unexpected downtimes and inefficiencies of the sugar industry. The present paper suggests an IoT monitoring system based on the cloud that will fit the needs of sugar factory in terms of sugar temperature, pressure control, and equipment conditions monitoring in real-time. Through predictive maintenance concepts, the system will strive to predict possible equipment breakdowns hence minimizing both the downtime and maintenance expenses. The combination of cloud computing will provide scalability and access to data, which will enhance responsible decision-making. The method has major benefits of efficiency in operations and quality of the product when compared to the traditional practices.