Dr. Henning Löser, Head of the Audi Production Lab in Germany, delivered a fascinating keynote address at the 2020 ARC Industry Forum on how Audi is helping shape the future of automobile production through innovation, while maintaining the overriding need for stable and predictable production.
As mentioned in a previous ARC Insight, in his keynote, Dr. Löser explained that Audi strives to be innovative, but at the same time, the company is set up for stable, high-volume production. The company produced almost two million Audi-branded automobiles in 2018. This led to a dilemma. “We want to shape the future of production by being innovative; but production is very structural by its nature and production groups tend to be very conservative.” To resolve this dilemma, the company founded the Audi Production Lab (P-Lab) in 2012 to explore and test innovative production approaches in a non-intrusive environment. This ARC Insight delves deeper into Dr. Löser’s P-Lab discussion at the Forum.
Audi P-Lab: Achieving Innovation in a Traditionally Conservative Environment
Dr. Löser explained that while Audi has been building beautiful cars for decades, there was always the feeling that “shiny” and appealing new ideas were out there, but as yet unproven in actual production environments. He used the German term, “ideenkultur,” which loosely translates to a “culture of ideas” to describe a culture of creativity, of new prototypes, and of speed that could help shape the future. “You can only do that by being innovative, by trying out new things,” he commented. But on the production side, you have a culture that’s very structural and organized where people tend to focus on meeting their quotas rather than exploring new technologies.
To overcome this mindset and enable the company to address problems from new angles, including using creative ideas coming out of the universities, the company founded the Audi Production Lab in 2012. According to Dr. Löser, the Audi P-Lab became the “zipper” that brings together the tightly organized and stable world of production, with the creative and fast-moving innovation world. The P-Lab combines the best of both: the speed and creative spirit needed for innovation, plus the structure and stability needed for production. Dr. Löser stressed that it does so by networking the company’s expertise, rather than networking organizations. According to Dr. Löser, “Trying out something new often involves breaking the rules. The P-Lab provides a safe space to do that.”
Connecting Production Data, Quality Measurements, and Process Knowledge
Dr. Löser discussed a representative proof-of-concept project developed in the Audi P-Lab that is being rolled out to the company’s production sites in Germany and elsewhere around the world. The project evaluated the potential business value of using predictive analytics to further improve the company’s spot welding operations. “Spot welding is the probably most well-known joining technology in car production; it seems like we’ve been doing it forever,” Dr. Löser said. “So, what have we achieved so far? If we look at spot welding, it's the main joining technology in our body shops. You have around 5,000 spots per car. The equipment availability is at 99.9 percent and, with a good maintenance crew, you can add on several additional ‘nines.’ This is already great technology, so is there a business case for using predictive analytics?” According to Dr. Löser, “The answer is yes, because no technology is 100 percent.”
Dr. Löser characterized the industry’s current quality inspection process for spot welding as performing manual ultrasonic inspections on random samples. If the ultrasonic testing should reveal any bad welds, you go back into the process and adjust the parameters. He explained that the idea here was to see if this process could be improved by reducing the need for manual ultrasonic inspections. To do this, “We started looking outside of the box.”
The P-Lab worked with Intel, one of Audi’s technology suppliers, to help it develop a proof of concept for driving operational improvements by tapping into existing data. “While, initially, we thought that the biggest challenge would be to devise the AI algorithms needed to gain insight, that turned out not to be the case.” Dr. Löser explained that the biggest problem faced was getting standardized access to the machine data and then coupling the data with the production process.
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Keywords: Audi Production Lab, Innovation, Stable Automobile Production, Predictive Analytics, Edge Computing, Intel, ARC Advisory Group.