Revolutionizing Tractor Manufacturing: A Case Study in Advanced Inspection Technology
Client: A prominent multinational automotive manufacturer specializing in car production and tractor manufacturing, headquartered in Mumbai, India.
Problem: The Tractor division produces a diverse range of tractor variants and engine parts, many of which contain complex features and components challenging for human quality inspectors to reliably assess. They initially installed a Robotic Inspection system with a traditional vision system tailored for feature identification by variant. However, this system struggled with environmental factors like water, oil, and rust, leading to unreliable inspections, especially for intricate objects such as threaded holes and dowel holes. This resulted in false positives and negatives, impacting product quality
Solution: The company’s solution was a game-changer:
Advanced Inspection Camera (AIC) with Nvidia Xavier: The implementation of AIC technology on Nvidia Xavier dramatically improved the inspection capabilities.
DIY (Deep Inspection by Yantra) Software Framework: A customized deep learning framework, developed in-house, provided the flexibility to handle complex inspection tasks.
Desktop UI: A user-friendly desktop user interface allowed real-time monitoring and intervention.
Robot Interface on Modbus: Integration with robots improved inspection efficiency and precision
.PLC Interface on Modbus: Communication with Programmable Logic Controllers ensured seamless automation.
The results of this transformation were nothing short of outstanding:
100% Detection Accuracy: The new inspection system, trained using real images and deep learning techniques, achieved a remarkable 100% detection accuracy.
Elimination of False Positives and Negatives: The unreliable detection issues experienced with the traditional vision system were resolved, ensuring consistent and accurate inspections.
Enhanced Manufacturing Operations: The company’s Tractor division successfully aligned its operations with Industry 4.0 expectations, making it a pioneer in advanced manufacturing technology.
In conclusion, the company’s commitment to excellence in tractor manufacturing led to the adoption of cutting-edge inspection technology. This case study highlights how AIC technology and deep learning frameworks can overcome complex inspection challenges, resulting in improved product quality and positioning the company as a leader in the industry’s shift towards Industry 4.0 standards.