Design & Fabrication of Color Sorting and Metal Detection Conveyor System.

Abstract

This project presents the development and implementation of an automated color and metal sorting system designed to enhance industrial sorting processes. The system employs a conveyor belt equipped with integrated color and metal sensors to detect and classify objects based on their material composition and color properties in real-time. The sensors, strategically positioned along the conveyor belt, identify objects as they pass through the system. Detected objects are then categorized based on predefined criteria, such as specific color ranges and metallic or non-metallic properties. The system incorporates a robotic arm equipped with advanced control algorithms to ensure precise object handling. Once the sensors detect and classify an object, the robotic arm is activated to pick and place the object in designated bins or locations. The arm’s movement is optimized for speed and accuracy, enabling seamless integration with the conveyor system. This setup significantly reduces manual labor and increases operational efficiency in sorting tasks. The system is particularly suited for industries where accurate sorting of materials is crucial, such as recycling, manufacturing, and quality control. By combining color detection and metal identification, the system ensures high accuracy in sorting mixed materials, which is often challenging in traditional systems. Additionally, the modular design allows for scalability and adaptability to various industrial environments. Preliminary testing demonstrates the system's ability to handle diverse object types and sizes with high reliability and efficiency. The integration of sensors and robotics not only streamlines the sorting process but also minimizes errors, offering a cost-effective solution for industries aiming to optimize their operations. This study highlights the potential for advanced sensor and robotic technologies to revolutionize material sorting, paving the way for more automated and intelligent industrial workflows.