AI-Driven Weight Control System for Optimizing Feed Speed in Cutting Machines

Current packaging manufacturing processes often rely on manual handling of tasks that could be automated, such as adjusting cutting machines and managing packaging materials, leading to increased labor costs and operational inefficiencies. A significant challenge in these processes is the inability to anticipate when packaging drums are nearing depletion, resulting in untimely interventions that disrupt production. To address these issues, this paper proposes an innovative system that integrates Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The system utilizes a combination of automated weight adjustments and real-time monitoring of packaging material levels to optimize manufacturing operations. By deploying AI-driven visual counting algorithms and IoT-enabled sensors, the proposed solution aims to detect and respond to operational discrepancies promptly, significantly enhancing manufacturing efficiency, reducing downtime, and minimizing costs associated with manual interventions. Experimental results demonstrate the effectiveness of this approach, highlighting its potential for broader application in industrial environments.