Audi Boosts Efficiency with AI

Audi is leveraging artificial intelligence (AI) to enhance efficiency, quality, and innovation across its production and logistics operations. The automaker is integrating AI tools to streamline processes, reduce costs, and improve data management, marking a significant shift in its manufacturing strategy.

Gerd Walker, Board Member for Production and Logistics at Audi, highlighted the transformative impact of AI on the industry. According to Walker, AI is creating a more efficient and cost-effective production environment while maintaining high quality standards and supporting employees. Audi has launched over 100 AI projects in its production facilities, focusing on AI-supported quality monitoring and generative AI.

The primary goal is to harness the potential of AI and data in company processes, customer experience, services, and products. AI is already making a substantial impact in production and logistics by saving time and money. As production generates vast amounts of data, Audi is expanding its data organization to manage hundreds of petabytes, with thousands of gigabytes added daily.

AI Applications in Audi’s Production

Audi has introduced several AI applications to enhance its operations. One notable tool is “Tender Toucan,” which analyzes bids during tendering. This tool uses specifications to create requirements, find relevant sections in bids, and assess fulfillment. Employees verify the tool’s work, saving up to 30 percent of their time. “Tender Toucan” will be used for series production planning of drivetrains and high-voltage batteries and will be rolled out across Audi and the Volkswagen Group.

Another AI application, “IRIS,” is used at the Ingolstadt and Neckarsulm assembly plants. It uses cameras to ensure that labels with technical data are correctly attached to vehicles, verifying the content, language, component, and position. While employees still perform spot checks, “IRIS” saves about one minute of production time per vehicle.

In collaboration with Siemens, Audi has introduced “Weld Splatter Detection” (WSD) in the Neckarsulm body shop. This application uses AI to detect weld splatter on vehicle underbodies, which could cause cable breakages. Previously, employees manually inspected and removed the splatter. In summer 2025, a robotic arm will automatically remove the weld splatter, improving occupational safety and ergonomics.

Audi’s 360factory: A Data-Driven Strategy

Audi’s 360factory is a production strategy focused on connected, innovative, and sustainable manufacturing. The integration of AI is accelerating the transition toward a data-driven factory. Walker emphasized that AI helps utilize data in production, making the 360factory more efficient and adaptable to future demands.

The 360factory strategy aims to create a seamless production environment where data and AI work together to optimize every aspect of manufacturing. This approach not only improves efficiency but also supports Audi’s commitment to sustainability and innovation.

Building an AI Network

Audi has established an AI expert network and is collaborating with the Innovation Park Artificial Intelligence (IPAI) in Heilbronn, which is set to become Europe’s largest AI network. Audi will have an office at the new 23-hectare campus as an IPAI member. The Audi Böllinger Höfe site, a location for small series production, acts as a real-world laboratory for digital production technologies under the AI25 (Automotive Initiative 2025) framework.

The AI25 initiative is an innovation network focused on digital transformation in the automotive industry. Audi’s involvement in AI25 and its collaboration with IPAI underscore the company’s commitment to leveraging AI for future growth and competitiveness. By building a strong AI network, Audi aims to stay at the forefront of technological advancements and drive innovation in the industry.

In conclusion, Audi’s integration of AI in its production and logistics operations is a strategic move to enhance efficiency, quality, and innovation. The company’s focus on AI-supported quality monitoring, generative AI, and data organization is paving the way for a more efficient and sustainable future in automotive manufacturing.