Paper Contents
Abstract
In modern manufacturing, quality control plays a crucial role in ensuring product reliability and efficiency. This project, "Fault Detection Machine Using Sensors," aims to automate fault detection in tubeless tire stem valves using IR sensors, LDR sensors, and NPN inductive proximity sensors. The system detects three primary faults: inverted products, missing cores, and incorrect product length. When a fault is detected, the machine triggers a buzzer, light indicator, and stops the conveyor to alert the operator.The conveyor system operates using a 100 RPM Johnson Geared Motor (DC 12V) with a PWM motor speed controller for adjustable speed control. The structural framework is made of PVC foam board (Sunboard) and plywood, supporting pulleys, belt mechanisms, and sensors for stable operation.This project demonstrates automation in quality control, improving fault detection accuracy compared to manual inspection. By integrating sensor-based detection, the system enhances efficiency, reduces human error, and aligns with Industry 4.0 standards. The project was successfully completed over an 8-week schedule, including design, fabrication, circuit integration, and testing. The results highlight the effectiveness of sensor-based fault detection in automated production lines.
Copyright
Copyright © 2025 VISHNU RANGANNAVAR . This is an open access article distributed under the Creative Commons Attribution License.
