OEM : Automotive

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Wolfsburg, Lower Saxony, Germany


The Group comprises ten brands from five European countries: Volkswagen, Volkswagen Commercial Vehicles, ŠKODA, SEAT, CUPRA, Audi, Lamborghini, Bentley, Porsche and Ducati. In addition, the Volkswagen Group offers a wide range of further brands and business units including financial services. Volkswagen Financial Services comprises dealer and customer financing, leasing, banking and insurance activities, and fleet management.

Recent Posts

The Volkswagen Infinity Squeeze that Squoze


Before GameStop (NYSE: GME) captured mainstream attention regarding a short stock squeeze, an iconic industrial company, Volkswagen (ETR: VOW), briefly became the one of the most valuable companies in the world during a short squeeze of their own.

Assembly Line

Conveyor-Less Micro Factories for Urban Car Production

📅 Date:

✍️ Author: Seog-Chan Oh

🏭 Vertical: Automotive

🏢 Organizations: Arrival, eGo Mobile, Volkswagen

The automobile manufacturing value chain consists of a press shop, body shop, paint shop and assembly. The assembly process is different from other processes in terms of automation. The level of automation in press shops, body shops and paint shops is usually very high. Many are nearly 100 percent automated. However, final assembly is difficult to automate due to the complexity of the tasks and diversity of the parts.

One way to achieve mass individualization while maintaining various automation levels is to decouple final assembly from the value chain. The press shop, body shop and paint shop would continue as mass production centers in central locations, while final assembly would be carried out in separate micro factories located in urban areas. The assembly process does not need to be physically located with the other manufacturing processes. Instead, it can be moved to an urban area where the labor supply is elastic. Low-volume, high-mix production can be realized with this model.

An urban automotive assembly plant should be designed for maximum flexibility, minimal capital investment and asynchronous production. That points away conveyors and favors autonomous transport technologies. Two options are available: autonomous mobile robots (AMR) and VaaC. AMRs are vehicles that are equipped with on-board sensors to autonomously move vehicles or materials along predefined paths without the need for magnetic tapes on the floor. In VaaC, the EV guides itself through the assembly process. A sensor skid, temporarily attached under the EV, guides the EV based on local sensing and communication with a high-level fleet management system. The skid is designed to be easily removed at the end of the assembly. The skid body has a set of pins that temporarily engage with locating holes in the underbody. The skid is equipped with numerous sensors that detect objects around the EV.

Read more at Assembly Magazine

How Volkswagen and Google Cloud are using machine learning to design more energy-efficient cars

📅 Date:

🔖 Topics: Generative Design, Sustainability

🏭 Vertical: Automotive

🏢 Organizations: Volkswagen, Google

Volkswagen strives to design beautiful, performant, and energy efficient vehicles. This entails an iterative process where designers go through many design drafts, evaluating each, integrating the feedback, and refining. For example, a vehicle’s drag coefficient—its resistance to air—is one of the most important factors of energy efficiency. Thus, getting estimates of the drag coefficient for several designs helps the designers experiment and converge toward more energy-efficient solutions. The cheaper and faster this feedback loop is, the more it enables the designers.

This joint research effort between Volkswagen and Google has produced promising results with the help of the Vertex AI platform. In this first milestone, the team was able to successfully bring recent AI research results a step closer to practical application for car design. This first iteration of the algorithm can produce a drag coefficient estimate with an average error of just 4%, within a second. An average error of 4%, while not quite as accurate as a physical wind tunnel test, can be used to narrow a large selection of design candidates to a small shortlist. And given how quickly the estimates appear, we have made a substantial improvement on the existing methods that take days or weeks. With the algorithm that we have developed, designers can run more efficiency tests, submit more candidates, and iterate towards richer, more effective designs in just a small fraction of the time previously required.

Read more at Google Cloud Blog

Missing Chips Snarl Car Production at Factories Worldwide

📅 Date:

✍️ Author: Debby Wu

🏭 Vertical: Automotive

🏢 Organizations: Aptiv, Ford, General Motors, Honda, Infineon, NXP Semiconductors, Renesas Electronics, Toyota, TSMC, Volkswagen

Semiconductor shortages may persist throughout the first half as chipmakers adjust their operations, researcher IHS Market predicted on Dec. 23. Automakers will start to see component supply gradually ease in the next two to three months, China Passenger Car Association, which groups the country’s largest carmakers, said Monday.

Chipmakers favor consumer-electronics customers because their orders are larger than those of automakers – the annual smartphone market alone is more than 1 billion devices, compared with fewer than 100 million cars. Automaking is also a lower-margin business, leaving manufacturers unwilling to bid up chip prices as they avoid risking their profitability.

Read more at Bloomberg (Paid)