One application example: classic cars are no longer manufactured, making them rare and special on the roads. However, if something breaks on the vehicle, this special status quickly becomes a problem. This is because spare parts are naturally no longer produced. Industry 4.0 is set to change this: Production is changing to batch size one - to individual production. A new buzzword has long been in circulation: "Highly customized mass production".

So far, this individualized production is still largely a dream of the future. Researchers at the Fraunhofer Institute for Computer Graphics Research IGD are taking the vision of a batch size of one a big step closer to reality with a new 3D scanning system. The special feature of this system is that it scans components autonomously - in real time. For classic car owners with a broken component, this means that the defective component is provisionally glued together and placed on a turntable, which is located under a robot arm with the scanner. Everything else happens automatically: the robot arm moves the scanner around the component in such a way that it can capture the entire geometry with as few scans as possible. Depending on the size and complexity of the component, this only takes a few seconds to a few minutes. During the scan, intelligent algorithms create a three-dimensional image of the object in the background. A subsequent material simulation of the 3D image checks whether 3D printing meets the requirements in terms of stability. In a final step, the component is printed using a 3D printer and can be installed in the classic car.

The development achievement does not lie in the scanner itself, but rather in the combination of the scanner with view planning to create an autonomous overall system. This view planning also comes from Fraunhofer IGD. In it, algorithms use an initial scan to determine which subsequent scans are useful so that the object can be captured with as few scans as possible. This procedure enables the system to measure completely unknown objects independently and quickly. This is unique, as previous scanners either had to be taught or the CAD model of the component had to be available in order to recognize the position of the object relative to the scanner. Once the scanner had been trained for quality control (target/actual comparison) for one car seat, it would be able to scan the next 200 car seats because they would be largely identical in mass production. Conventional scanners are not very suitable for batch size one.

Thanks to these unique selling points, the autonomous scanner enables completely new applications, for example in production assistance or human-machine collaboration. pb