Design and Fabrication of Faulty Product Detection and Separation System
Year: 2025
Type: article
Abstract: The increasing demand for automated systems in modern manufacturing processes has driven the need for effective quality control solutions. This research focuses on the design and fabrication of a fault detection and separation system aimed at identifying and removing defective products from a production line. The proposed system integrates advanced sensors and automated mechanisms to ensure that only products meeting quality standards are passed for further processing or packaging. By automating this critical process, the system reduces human error, enhances production efficiency, and improves overall product quality. The system utilizes a combination of visual and sensor-based detection methods. High-resolution cameras or optical sensors capture images of the products moving along a conveyor belt. Image processing algorithms analyze the captured data to detect any defects such as cracks, dents, or dimensional inconsistencies. Additionally, weight sensors may be incorporated to identify any variations in mass, signaling potential flaws in the product. Once a faulty product is detected, an actuator mechanism, such as a robotic arm or pneumatic system, is employed to remove the defective items from the line. In the final phase, the research evaluates the performance of the detection and separation system through a series of tests. Results demonstrate the system's ability to accurately identify defects in real-time, ensuring minimal disruption to the production process. The findings suggest that this automated approach can significantly enhance manufacturing workflows, offering a reliable and scalable solution for industries seeking to implement advanced quality control measures. The paper concludes with recommendations for further improvements and potential applications of this system in various industrial settings. Key Words: optics, photonics, light, lasers, templates, journals
DOI: 10.55041/ijsrem43454
Authors: Mohit Lokhande, Sushant Masaye, Atharva Mane, Kiran Gunale, Amol J. Ghude, Trupti Trupti,, Bhavna Ingole, Dr. Usha Pawar, Pankaj Rathod
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409000640