DEVELOPMENT OF AN AUTOMATED AND INTELLIGENT CONTROL SYSTEM FOR THE POLYVINYL CHLORIDE DRYING PROCESS

The drying process is a critical stage in polyvinyl chloride production, directly influencing product quality, energy consumption, and operational efficiency. Conventional drying systems often rely on fixed control strategies that are unable to effectively handle the nonlinear and dynamic nature of polymer drying. This study presents the development of an automated and intelligent control system for the PVC drying process aimed at improving energy efficiency and moisture uniformity. The proposed system integrates real-time process monitoring, programmable logic controller-based automation, and intelligent control techniques, including fuzzy logic and neural network-based moisture prediction. Key drying parameters such as air temperature, humidity, and airflow rate are continuously monitored and adaptively regulated. Comparative experimental analysis was conducted between conventional control and intelligent control modes under identical operating conditions. The results demonstrate that the intelligent control system significantly reduces drying time and energy consumption while maintaining stable operating conditions and achieving uniform final moisture content. The predictive capability of the neural network model enables proactive control actions, enhancing process reliability and product consistency. Overall, the findings confirm the effectiveness of intelligent control technologies in optimizing industrial PVC drying processes and supporting the implementation of smart manufacturing principles.