Audi is employing artificial intelligence to revolutionise visual inspection in production

2 mins read

Car giant Audi plans to apply machine learning (ML) in series production, using software it has developed to recognise the finest cracks in sheet metal parts – automatically, reliably and in a matter of seconds.

Audi inspects all components after production in its press shop. In addition to visual inspection by employees, several small cameras are installed directly in the presses. These cameras evaluate the captured images with the help of image-recognition software. But this process will soon be replaced by an ML procedure. Software based on a complex artificial neural network operates in the background of this innovative procedure, with the software detecting the finest cracks in sheet metal and reliably marking the spot.

Says Jörg Spindler, head of the Competence Center for Equipment and Forming Technology:“We are currently testing our automated component inspections for series production at our Ingolstadt [Bavairia, Germany] press shop. This method supports our employees and is another important step for Audi in the transformation of its production plants into modern smart factories.”

The solution is based on deep learning, a special form of machine learning that can operate with unstructured and high amounts of data, such as images. The team spent months training the artificial neural network with several million test images. The biggest challenges were, on the one hand, the creation of a sufficiently large database, and on the other, the so-called labelling of the images. The team marked cracks in the sample images with pixel precision – the highest degree of accuracy was required. But now the neural network learns independently from the examples and detects cracks even in new, previously unknown images. The database consists of several terabytes of test images from seven presses at Audi’s Ingolstadt plant and also includes others from Volkswagen plants.

Explains Frank Loydl, chief information officer at Audi AG: “Artificial intelligence and machine learning are key technologies for the future at Audi. With their help, we will continue to sustainably drive the digital transformation of the company. In this cross-divisional project, we are jointly developing a production-ready solution that Audi will use exclusively in the company and which is unique in the market.”

The software was mainly developed in-house, from the idea to the finished prototype. Since mid-2016, the innovation department of Audi IT has been working hand in hand with the Production Technology division of the Equipment and Metal Forming Technology Competence Center.

In the future, quality inspection using ML will replace the current optical crack detection with smart cameras, because the current method involves a great deal of manual effort. Whether doors, engine bonnets or bumpers – the camera currently has to be reconfigured for every new component produced in the press shop. In addition, false detections regularly occur, since the simple algorithms of the image-processing program are highly dependent on ambient factors such as lighting conditions and surface properties.

In the future, it will also be possible to apply the ML approach for other visual quality inspections. If a sufficiently large number of labelled datasets are available, the system can also support paint shops or assembly shops, for example.