A global automotive parts manufacturer approached us as their outdated inspection methods were costing more than just once. They were unable to catch defects in real-time with their outdated 2D systems. We developed and launched a 3D machine vision system. This system enabled high- speed automotive production lines. We transformed their production line into an error free powerhouse with the help of robotic integration.
Automotive
AI/IoT/Emerging Tech
The process began with a detailed production floor audit and lighting analysis. Afterward, we carefully chose the right 3D vision sensors and calibrated for various inspection points. This ensured compatibility with speed and lighting variability.
Custom-trained deep learning models were used to identify surface anomalies, shape defects, and geometric inconsistencies. Each model was optimized for parts like engine casings, axles, and door panels.
The vision system was integrated directly with robotic arms and PLCs (programmable logic controllers). This proved to be efficient as it enabled instant part rejection and alignment correction without human intervention.
We built a data pipeline that streamed inspection outcomes to their Manufacturing Execution System (MES) for real-time dashboards and downstream analytics.
Quality checks depended heavily upon human operators and 2D vision setups. They had several issues such as inability to spot fine surface flaws and alignment issues. Whereas manual checks caused bottlenecks that slowed down fast-moving lines. All these issues showed that there was a need for a flexible 3D vision solution. The system should be able to operate in real-time and is capable of smoothly integrating into their robotic and data infrastructure.
Maintaining precision at 300+ parts/hour meant we had to optimize processing times to under 200ms per inspection. We used edge devices with GPU acceleration and pipeline parallelism.
The system had to inspect a wide variety of parts—from compact clips to full body panels. We trained models with wide variance and used multi-sensor setups with dynamic focal length adjustment.
This section shows how our advanced inspection systems have improved quality control and efficiency.
Defects caught earlier, faster, and automatically meaning less rework and smoother workflows.
Surface defects and geometric issues were identified with sub-millimeter accuracy.
Inspection speed improved drastically without compromising precision, letting the team process more parts in less time.
At OrangeMantra, we don’t just build systems—we build smarter factories. Our 3D machine vision solution didn’t just inspect; it transformed how quality is done on the shop floor. With vision-driven intelligence and real-time control, we helped our client step confidently into the future of Industry 4.0.