Development of an Automation and Intelligent Control System for the Polyvinyl Chloride (Pvc) Drying Process
Key Points
The aim is to develop an automated control system to enhance the PVC drying process by optimizing key parameters.
Developed an automation and intelligent control system integrating sensor-based monitoring and machine learning algorithms.
Utilized mathematical modeling to adapt control to variations in PVC physicochemical properties.
Focused on optimizing energy consumption and improving product quality.
Successfully reduced energy consumption in the PVC drying process by optimizing control parameters.
Improved product quality metrics such as residual moisture and structural uniformity after implementation.
Achieved real-time adaptive control through integration of machine learning algorithms.
Abstract
Drying of polyvinyl chloride (PVC) is a critical stage in polymer processing that significantly influences its physicochemical properties, including residual moisture, bulk density, thermal conductivity, and structural uniformity. This paper presents the development of an automation and intelligent control system for the PVC drying process aimed at optimizing process parameters, reducing energy consumption, and improving product quality. The proposed system integrates sensor-based monitoring, mathematical modeling, and machine learning algorithms to enable adaptive control based on real-time variations in physicochemical properties of the material.