Working in concert

Utilising cutting-edge technology has always been an integral part of the Audi brand, and as a result, it’s hardly surprising that Audi is one of the first vehicle manufacturers to employ Artificial Intelligence (AI) and machine learning throughout its manufacturing precesses.

But despite the increase in the use of these advanced technologies, the role of people in the production process will always be integral according to the brand’s AI experts.

“The term 'artificial intelligence’ makes it sound as though a computer were trying to imitate human intelligence,” says Rüdiger Eck, one of those tasked with implementing the technology at Audi.

“But in reality, AI today means running a very fast statistical evaluation that makes data-based decisions.

His colleague, Dr Stefan Keckl agrees that AI may conjure images of systems that has little resemblance to the actual technology.

“When we train AI algorithms today, a person selects the data and determines what the AI will learn. This lets us transparently show, at any time, how the AI was created.”

Production is the perfect environment, where it not only simplifies and automates processes, but ensures product quality and increasing profitability. Audi currently uses artificial intelligence in production at the Neckarsulm site, where it monitors the quality of spot welds and also in the Ingolstadt press shop where it is employed to check images of pressed parts to detect cracks.

But if AI is already automating processes in production, aren’t future scenarios of factory floors devoid of people realistic after all? The answer is a resounding ‘no’ according to Eck.

“Take assembly work in automotive production for example,” he says. “The tasks this entails involve a complex mixture of cognitive performance, physical movement, and sensory perception. Let’s not underestimate that complexity, where humans are clearly better than robots. AI, on the other hand, can take over jobs that humans are not so good at, such as analysing large amounts of data or repetitive work.”

In the future, the strengths of AI will be seen in four main areas says Eck.

“First, it can improve product quality by warning when errors occur. Second, it can prevent errors by relieving people of repetitive work that doesn’t add value. Third, AI can optimise processes by revealing correlations that people don’t recognise. This lowers costs by increasing efficiency. And last but not least, AI can frequently help increase the output or performance of processes or machines.”

There are currently some 60 data-savvy people at Audi working on how best to leverage AI within the production processes, with around a dozen of them working on machine learning and data science.

“There are also a lot of people who’ve switched into the team who bring a lot of passion and knowledge of production processes,” ays Keckl. “They are continuing their training in AI, and it works really well.”

“We are currently the ones developing AI systems for production,” adds Rüdiger Eck. “But in order for AI to reach its full potential, we need to embrace making data-based decisions on a company-wide scale. We need to and want to become a data-driven company.”