Case Studies
Specialised in industrial vision for more than 25 years, Visio Nerf was able to set itself apart, and thanks to products with increasingly higher levels of performance, the know-how of its qualified personnel and the rigour in its commitment to its customers, now offers an innovative range of 3D sensors. These new scanners called Cirrus make it possible to respond to often complex applications in complete simplicity. From locating parts in bulk for loading machine tools, to correcting robot trajectories for depositing putty or a windscreen on a vehicle, without forgetting parts inspection directly on the production line, these high-end products push back the limits in industrial vision in order to offer you maximum performance and return on investment on your production lines.
Content Filed Under:
Industry:
Aerospace
, Automotive
, and Robotics
Aerospace
, Automotive
, and Robotics
Application:
In Process Alignment
, In Process Verification
, and Material Handling
In Process Alignment
, In Process Verification
, Material Handling
, Measurement (Non Contact)
, Process Control
, Simulation/3D Modeling
, System Analysis & Verification
, and Vision Guidance for Robotics
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Robot Guidance: Automated Wheel Installation
POSTED 02/19/2020
| By: Alexie, Product Manager
The Application
The manufacturer in the automotive sector was looking for a solution for the wheel installation in order to improve processes in its factory. This manufacturer was using a manual system that required four workers to pick-up and mount each tire on the rotor; two workers would work on each side of the wheel during the installation process.
This application has been realized by Bluewrist.
The Challenge
There were a number of challenges to address when designing an application that would improve performance, process, and quality. These challenges relate to both the rotors and the processes involved in fitting the tires.
- Over 60 different rims are used with different types of surfaces (dark, matte, glossy), which makes 2D camera systems difficult to implement because of the effect of lighting solutions on the different types of surfaces.
- The bolts are preinstalled on each router. Each bolt cap has a small surface area, which means a 3D, high-resolution vision system is essential to accurately locate the point cloud for each bolt cap. That is why our partner has chosen the cirrus3D by VISIO NERF to develop its application.
- During installation, the rotor has a random rotation, which means that the bolts are in a different position for each installation, requiring a solution that will for and identify the bolt location.
- Because the rotor can rotate up to 15 degrees in both directions along the car, the solution also needs to be able to achieve 3D matching or a large point cloud.
- In addition to these technical factors, the part is heavy, and the cycle time is limited, with only 3.5 seconds available for the full point cloud grab and process.
The Solution
The solution implemented is done with a high-resolution blue structured light 3D camera, the cirrus3D by VISIO NERF. The 3D sensor is combined to the Bluewrist 3D Vision Robot Guidance solution software. And two Fanuc robots with a seven-axis linear slide are used for the robotic aspect. Using this system, the point clouds of the wheel and the rotor are matched to the corresponding CAD model with remarkable accuracy. The vision system can achieve +/? 0.3 mm accuracy in XYZ and +/? 0.3 degrees in WPR.
The Results
The full solution is scalable from a few hundred to thousands of cars per day as required by a manufacturer’s production requirements. Our client’s current production run rate is 250 cars per day, and the wheel installation system consistently achieves 99.5% uptime. The application can pick up the wheel and install it onto the rotor with multiple features covering the functionality required to process different surfaces, fitting positions, and bolts.
The 3D vision system is able to capture a high quality of cloud of points with different types of material. The system is robust to the color and brightness of the part: dark matt surface for the tire, bright shiny surface for the rotor for example. Moreover, the sensor is designed to make possible the simultaneous acquisition in a same scene of parts made of multiple materials. With a vision processing cycle time of 3.5 seconds, efficiency is much improved, the initial problems have been resolved, and the process no longer requires any worker involvement.
