Audi continues scaling up AI in production and logistics, reducing lead times and streamlining logistics
Audi is scaling up its use of artificial intelligence (AI) in production and logistics to improve processes in its factories and throughout its entire value chain, in line with its digitalisation plans – a key pillar of its 360factory strategy.
Audi has shared more about its recent deployment of AI and digital technologies, from scaling up its cloud platform to deploying robots to demonstrating how entire process chains could be digitised and automated. Through end-to-end data integration, from suppliers through to assembly, Audi intends to improve production processes, with potential implications for supply chain and logistics operations.
Digitalisation and automation is one of the five key pillars of Audi’s 360factory strategy. Unveiled in 2022, this strategy was designed as a holistic framework covering both manufacturing and logistics, aiming to drive improvements across five key areas: EV transition; order-to-delivery; decarbonisation and resource efficiency; digitalisation and automation; and teamwork.
As part of this strategy, Audi is focusing on leveraging digital solutions to enhance efficiency and to create more flexible manufacturing and logistics processes.
“Artificial intelligence is a quantum leap for efficiency in our production. With our AI and digitalisation roadmap, we are transforming our plants into smart factories where AI acts as a partner, providing our employees with tailored support," said Gerd Walker, member of the board of management for production and logistics at Audi. “The first AI-controlled robots are taking over tasks that are ergonomically strenuous, and chatbots are providing additional relief.”
End-to-end supply chain integration
One forward-looking project Audi has highlighted is its ‘Next2OEM’ project, in which it is working alongside 10 partners at its headquarters in Ingolstadt, Germany, to demonstrate how the production and assembly of a wire harness can be completely digitalised and automated – from the supplier to installation in the factory. Audi has noted that to date, less than 10% of wire harness production and assembly is automated across the industry.
This demonstrator, funded by Germany’s Federal Ministry for Economic Affairs and Energy, will map the entire process chain, from wire harness production and pre-assembly in the centre console with automation-compatible connectors to automated installation in the vehicle.
The OEM describes the benefits of this project as “considerable”. It says this will lead to less logistical effort and significantly shorter lead times for changes, which can be cut down from weeks to a matter of minutes.
In terms of next steps, Audi plans to incorporate the knowledge gained into the large-scale production of future vehicle projects.
Audi references the project linking supplier production more closely to vehicle requirements, which has the potential to improve sequencing accuracy on the production line. BBy reducing lead times from weeks to minutes and improving data integration across the process chain, Audi can improve accuracy, as well as end-to-end visibility across the supply chain.
Data platforms enabling supply chain visibility
Underpinning Audi’s deployment of AI in different use cases is a policy of cross-plant collaboration on AI and digitalisation, with the Audi production network relying on “scaling and intensive sharing”.
The automaker has highlighted two examples of this from different parts of the world. Firstly, it noted that the Audi Hungaria team “systematically assesses its value chain to identify potential for digitalisation” and that AI is helping to improve the transparency and efficiency of production processes at its plant in Györ, Hungary.
Secondly, it pointed towards Mexico, where management at Audi México take advantage of an AI-supported tool which produces production reports, displaying key figures in real time. This information supports the team in making decisions based on precise, up-to-date operating data from the San José Chiapa plant.
Audi’s approach reflects a shift towards a more integrated, cross-plant supply chain model, where decisions are informed by real-time, standardised data across its global production network.
Benefits of access to real-time production data
A central theme in Audi’s AI rollout is the use of real-time production data to connect shopfloor operations more closely with upstream supply. By providing workers and systems with continuously updated vehicle specifications, Audi is replacing more static planning processes with a dynamic, data-driven approach that can respond instantly to changes in demand or configuration.
From a logistics perspective, access to production data in real time could help suppliers and logistics service providers to better align parts supply with actual production requirements, improving accuracy and reducing risk.
The result is a stronger foundation for both JIT and JIS delivery. Instead of relying on fixed schedules or manual intervention, material flows can be adjusted in line with live production data, improving sequencing precision while reducing the need for buffer stock. Meanwhile, access to this data can also enable earlier detection of issues, therefore allowing earlier intervention to improve efficiency and limit disruption.
More broadly, Audi’s approach points to a shift in how production data is used across the supply chain. Rather than being confined to the factory, real-time information is playing a broader operational role across the production network, supporting more responsive, accurate and synchronised logistics execution from supplier to line-side operations.
More digitalisation in Audi's production operations
In addition to supply chain applications of AI, Audi has furthered its digitalisation journey through the implementation and scaling up of a number of technologies in its production operations.
Audi is currently shifting production control and automation systems to a cloud-based edge architecture – more specifically Edge Cloud 4 Production (EC4P). According to Audi, EC4P makes it possible to combine conventional automation technology with flexibility and computing power from the cloud.
As a result, the automaker should be able to simplify processes and introduce introduce new functions more quickly, while eliminating the need for more than 1,000 industrial PCs. This, it has said, “makes processes more stable, reduces maintenance costs, and increases IT security”.
In doing this, Audi has said that it is “setting the next benchmark in fully networked factory automation and at the same time laying the foundation for the widespread use of AI in production”.
At its Neckarsulm site in Germany, Audi has also deployed the Weld Splatter Detection (WSD) system, which detects weld spatter on the underside of a car body and marks it with light. And following a recent upgrade to the system, the physically demanding task of grinding down weld spatter can now be carried out by a robot arm.
The WSD is set to run on the EC4P in the future, enabling even greater flexibility and scalability. Volkswagen Group's first AI-supported weld spatter detection system will soon go into series production at six plants in Ingolstadt.
