Audi Scales Up AI in Production with Cloud Platform and New Use Cases
Audi is deploying a large cloud platform across its production environment to control systems, eliminating over 1,000 industrial PCs and introducing AI for tasks like weld splatter detection and predictive maintenance.
over 1,000
around 100
less than 10%
What Happened
Audi is putting its Edge Cloud 4 Production (EC4P) into operation across its production environment, combining automation technology with cloud computing. This simplifies processes, reduces hardware, and enables faster introduction of new functions. In vehicle assembly at German plants, worker guidance is now centrally controlled from the cloud, providing real-time information to employees.
“Artificial intelligence is a quantum leap for efficiency in our production. With our AI and digitalization roadmap, we are transforming our plants into smart factories where AI acts as a partner, providing our employees with tailored support.”
- Weld Splatter Detection (WSD) to detect and grind weld splatter
- ProcessGuardAIn for real-time monitoring and anomaly detection
- AI-supported dryer operation in the paint shop for energy efficiency
Over 1,000
Cloud-based control replaces local computers.
Audi is also working with partners like IPAI Heilbronn and, in the Next2OEM project, aims to digitize and automate wiring loom production and assembly, which is currently less than 10% automated industry-wide.
Why this matters
By moving to cloud-based production control and AI, Audi aims to increase efficiency, reduce costs, and improve quality, setting a benchmark for the automotive industry's digital transformation.
Terms in This Story
- Edge Cloud 4 Production
- A cloud platform for controlling production systems in factories.
- Virtual PLC
- Software-based programmable logic controllers replacing hardware controllers.
- Weld Splatter Detection
- AI system that detects and removes weld splatter on car bodies.
- ProcessGuardAIn
- Audi's AI solution for monitoring manufacturing processes and detecting anomalies.
Summarised from the linked release; details can be imperfect — always verify against the original source.