AI-based image recognition in assembly - BMW Group Plant Munich

AI projects in assembly mainly focus on automated image recognition.

Here, the technology is used to evaluate images of a component and compare them in milliseconds with hundreds of other images from the same sequence.

The system then identifies any deviations from the norm, such as parts that are incorrectly positioned or fitted, or absent.

At Plant Munich, automated image recognition allows the production team to identify whether the hazard warning triangle, wiper caps and door sills have all been correctly fitted to each car.

Previously, small bubbles in the foil cover of a door sill were often enough to prevent the conventional camera gates from seeing if the logo on the door sill was correct.

But now an associate photographs each part concerned in turn and can even use the mobile equipment to check parts that are more difficult to access.

Distance, angle and light hardly have any effect on AI evaluations, which reveal within fractions of a second whether everything is in place or not.

The AI system is trained by associates.

They start by photographing the component concerned from various perspectives and marking potential deviations on the images.

This allows them to develop an image database that can be used to build up a neural network for evaluating the images.

Evaluations are carried out fully automatically, and the machine decides by itself whether or not a part meets all the specifications.