Design and Development of Pelletizer Automation using Load Control
This research study aims to design and implement an advanced automation system for pelletizers, integrating load control technology to optimize pellet production processes. Pelletizers are widely used in industries such as agriculture, food processing, and pharmaceuticals for converting raw materials into uniform pellets. However, traditional pelletizer systems often lack precise control over load conditions, leading to inefficiencies, inconsistencies, and potential equipment damage. Incorporation of load sensors into the pelletizer system to monitor the load exerted on the pelletizing blades or rollers in real-time. Load sensors will provide accurate feedback on the compression force applied during the pelletization process, enabling precise control and adjustment of pelletizer parameters. Implementation of an intuitive current rating and load to facilitate the controlled automation of pelletizing motors. A controller will provide operators with control options, real-time monitoring of load conditions, status updates, and alarm notifications, ensuring ease of operation and troubleshooting. Development of intelligent control logic and algorithms to optimize pelletization parameters dynamically based on load feedback and quality requirements. The proposed system will be capable of adjusting process parameters in real-time to accommodate variations in raw material properties and production conditions. Incorporation of data logging capabilities to record key process parameters, load profiles, and production metrics over time. Data analysis tools will enable performance evaluation, process optimization, and predictive maintenance scheduling. the paper aims to demonstrate the feasibility and advantages of integrating load control technology into pelletizer systems, leading to enhanced efficiency, precision, and safety in pellet production processes.
Authors
- S. Vijayachitra
- D Mukila
- L B Mukesh
- G Nithesraj
- K. Prabhu
Publication Details
- Published
- 2024-09-18
- DOI
- https://doi.org/10.1109/icosec61587.2024.10722053
- Citations
- 1
- Primary Topic
- Wireless Sensor Networks and IoT
- Type
- article
- Field-Weighted Citation Impact
- 0.33