3D vision makes it possible to capture optimal process parameters during a pilot series carried out by an operator, in order to have them reproduced in large series later by an automated system.
Let’s take the case of an operator presenting a steel rod under a forging press. Depending on the position of the rod, the material will not fill the forging die in the same way. The first tests will therefore determine the best position of the rod, by a trial-and-error process, and then the operator will try to keep it identical throughout the series.
In addition, other parameters, such as striking force or heating temperature, are optimized.
The added value of the expert operator is clearly in the first phases, to identify the right parameters.
Once this is done, he can make way for a robot, which will grab billets from the crate, heat them up and position them in the die for striking. The operator can then control the process and, once it is validated, start another run on another machine while the robot finishes the job.
Acquiring the correct position of the part in the forging die at the time of striking, and reproducing it, is one of the many contributions of 3D vision to this process.