Case Study | Transfer Technology 3D Vision-Guided System: Tackling Challenges of Cross-Stacked Aluminum Ingot Handling

Traditional manual loading and unloading of aluminum ingots comes with numerous drawbacks: low efficiency, intensive labor, harsh working environments, high error rates and safety risks stemming from human operation. These factors restrict productivity growth and stable operation quality, while raising corporate operating costs and occupational health risks for workers.

Therefore, the customer adopted an intelligent combination of 3D vision and industrial robots to deliver an efficient, precise, flexible and cost-effective solution for aluminum ingot picking.

01 Project Difficulties

Aluminum ingots feature inconsistent surface appearance and severe high reflectivity.

Ingots are cross-stacked and form large-size stacks.

02 Technical Highlights

This project adopts the Epic Eye Laser L camera, Epic Pro software and KUKA industrial robot for coordinated operation to realize automated aluminum ingot handling. As the "eye" of the solution, the Epic Eye Laser L boasts a broad field of view and precise measurement capacity to capture accurate pose data of aluminum ingots. Serving as the "brain", Epic Pro software undertakes intelligent recognition and path planning. The KUKA robot acts as the "arm" to perform precise picking and safely place aluminum ingots to target positions.

±2 mm Recognition Accuracy, Robust Against High Reflectivity

In automated aluminum ingot loading and unloading, the laser camera delivers outstanding performance coping with highly reflective surfaces, bringing tangible benefits to the customer.

The Epic Eye Laser L maintains high-quality imaging under intense ambient light over 120,000 Lux. It reliably handles the high reflectivity of aluminum ingots and precisely acquires 3D data. The solution improves picking accuracy and throughput, reduces recognition failures triggered by surface reflection, minimizes material waste and production downtime, and delivers enhanced production stability and cost advantages.

Empowered by Intelligent Algorithms, Adaptable to Cross-Stacked Workpieces

When handling large stacks of cross-stacked aluminum ingots, the 3D vision system embedded with advanced AI and deep learning algorithms can identify ingots and accurately estimate object poses.

It raises the recognition success rate and guarantees stability and safety during handling of large stacks. Intelligent trajectory planning algorithms calculate optimal picking paths to prevent collisions and enhance operational stability, enabling reliable performance even in confined spaces with heavy mechanical interference.