Audi is signing another pilot project on the use of artificial intelligence (AI-Artificial Intelligence) in production. In the project carried out at the Neckarsulm facilities, the quality of spot welds in high-volume production is controlled by artificial intelligence.
The system operates as a part of the Industrial Cloud, developed by Volkswagen Group together with Siemens and Amazon Web Services (AWS), and is planned to be used in other areas in the coming periods. is signing a new pilot project in its facilities. The project is based on the quality control of spot welds with artificial intelligence in models with a high production quantity. The parts that make up the body of an Audi A6 are joined by around 5 spot welding. Until now, the control of these point welds was carried out by production personnel, using random analysis and manual ultrasound methods. With the new project, experts from the fields of production, innovation management, digitization planning and IT are testing a much smarter and faster way to determine the quality of spot welds. As part of the “WPS Analytics” pilot project at their Neckarsulm facility, the team led by Mathias Mayer and Andreas Rieker has automatically and genuinely detected quality anomalies. zamMichael Haeffner, Head of Production and Logistics Delivery Management Digitization of AUDI AG, who gave information about the project and said that they are very happy with the point reached at the moment, said, “A pilot for digital production and logistics at Volkswagen Group. As a facility, our aim is to develop and test digital solutions to be used in the mass production phase. With the use of AI, we are testing here an important key technology that will future-proof Audi and its position.” The algorithm, which is the basis of the project that is tried in the body production of the Audi A6/A7 models, which are still produced at the Neckarsulm facility, has a graphical user interface and an application used for quality analysis. With the project, it is aimed that this algorithm will analyze almost all the welding points made during body fabrication in the future. Thus, it is also aimed to automatically control the quality of welding processes and ensure that they can be continuously optimized in the future.
WPS also offers opportunity for Preventive Maintenance
Mathias Mayer, who stated that they have been working on the use of AI in production for five years, said, “The use of WPS Analytics is an exciting opportunity. The algorithm also acts as a blueprint for other connected applications in production. It also allows us to make advances in existing digital solutions such as 'Predictive-Predictive Maintenance'.” said.
Solutions are available throughout the Volkswagen Group
As part of the Volkswagen Group's Industrial Cloud, Audi is leading the way in this direction. The system, whose primary purpose is to increase efficiency and reduce costs, brings together production data from the group's factories around the world on a single powerful digital platform. Each connected site is able to download the applications required for its machines, tools and systems directly from the Industrial Cloud, just like in an application store, thus producing its products even more efficiently. After the success of the “WPS Analytics” algorithm and panel in Neckarsulm, it is planned to be deployed to multiple factories across the group. Audi plans to launch another application, which uses an algorithm to make production processes more efficient, at the Ingolstadt press plant early next year. An artificial intelligence will be used to detect quality defects such as cracks in the vehicle body. This project is the same zamIt will also set an example for the Automotive Initiative 2025 (AI25), the global competency network where Audi has established digital factory transformation and innovation. Audi's ultimate goal is to make production and logistics more flexible and efficient through digitalization. Audi also helps its employees with its innovative technologies, freeing them from tiring physical tasks and monotonous manual tasks.
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