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.
Through the Next2OEM project, Audi is working with partners to demonstrate how the production and assembly of a wire harness can be completely digitalised and automatedAudi
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
Responsible use of AI at Audi
Audi has emphasised that it is committed to using AI
responsibly and that this is outlined in its code of conduct, which is binding
for all employees. Its AI policy centres around three guiding principles:
respect, security and transparency.
With these principles, Audi intends to help exploit the
potential of AI, while protecting the company and its employees, as well as
respecting the rights of users.
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
Audi is putting the EC4P into operation in the large-scale production environmentAudi
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.