OEM : Automotive
The special fascination of the BMW Group not only lies in its products and technology, but also in the company’s history, written by inventors, pioneers and brilliant designers. Today, the BMW Group, with its 31 production and assembly facilities in 15 countries as well as a global sales network, is the world’s leading manufacturer of premium automobiles and motorcycles, and provider of premium financial and mobility services.
BMWs to Drive Themselves During Production
BMW Group project manager Sascha Andree explained: “Automated driving within the plant is fundamentally different from autonomous driving for customers. It doesn’t use sensors in the vehicle. In fact, the car itself is more or less blind and the sensors for maneuvering them are integrated along the route through the plant.”
Initially, the vehicles will only move through the assembly area and then to a parking area, ready for their onward journey by train or truck. But in reality, it is possible to use the tech as soon as the cars are capable of driving independently in the production process.
BMW Creates Fully Automated Production Lines for 3D Printed Car Parts
By utilizing systems made up of laser powder bed fusion (LPBF) platforms, combined with AI and robotics, that it has developed, the IDAM consortium can print 50,000 series parts a year, as well as 10,000 new and individual parts. Opened in 2020, BMW’s campus at Oberschleißheim has 50 3D printers for both metal and plastics. Aside from investing in a variety of 3D printing startups, including Desktop Metal and Xometry, the company also employs HP MultiJet Fusion (MJF) and EOS machines, among other brands.
Driving Toward A Sustainable Future
A physics-based electronics reliability assessment tool, Sherlock enables Schirmer and his team at BMW to assess the performance of PCBs under a range of thermal cycles, including temperature changes and static temperatures. BMW can also test PCB components for shock, random vibration, and steady mechanical loads.
Given the growing demand for new EV designs and product features, the Department of Power Electronics is under pressure to complete its reliability studies quickly — but without compromising analytic depth and breadth. “With Ansys Sherlock, I’m able to manage 90 to 95% of my analytic modeling with a single tool that integrates easily with Ansys Workbench, Ansys physics-based solvers, and ECAD tools,” says Schirmer. “I’m grateful to have a partner who understands my needs and responds to them with the right capabilities.”
BMW uses Nvidia’s Omniverse to build state-of-the-art factories
BMW has standardized on a new technology unveiled by Nvidia, the Omniverse, to simulate every aspect of its manufacturing operations, in an effort to push the envelope on smart manufacturing. BMW has done this down to work order instructions for factory workers from 31 factories in its production network, reducing production planning time by 30%, the company said.
Product customizations dominate BMW’s product sales and production. They’re currently producing 2.5 million vehicles per year, and 99% of them are custom. BMW says that each production line can be quickly configured to produce any one of ten different cars, each with up to 100 options or more across ten models, giving customers up to 2,100 ways to configure a BMW. In addition, Nvidia Omniverse gives BMW the flexibility to reconfigure its factories quickly to accommodate new big model launches.
BMW succeeds with its product customization strategy because each system essential to production is synchronized on the Nvidia Omniverse platform. As a result, every step in customizing a given model reflects customer requirements and also be shared in real-time with each production team. In addition, BMW says real-time production monitoring data is used for benchmarking digital twin performance. With the digital twins of an entire factory, BMW engineers can quickly identify where and how each specific models’ production sequence can be improved. An example is how BMW uses digital humans and simulation to test new workflows for worker ergonomics and efficiency, training digital humans with data from real associates. They’re also doing the same with the robotics they have in place across plant floors today. Combining real-time production and process monitoring data with simulated results helps BMW’s engineers quickly identify areas for improvement, so quality, cost, and production efficiency goals keep getting achieved.
Expanding Omniverse: BMW Group Builds their Factory of the Future 2.0
Applying Artificial Intelligence to Paint Shop Robots
Häcker says that factories in the automotive industry have “enormous amounts of latent data about manufacturing processes, raw materials, and products. The key to leveraging these data assets is connectivity with the right interface at the control level to get at the information provided by robots, ovens, cathodic electrocoating systems or conveyor technology. Operators in existing plants are often constrained because most of their systems do not have connectivity and the right interface for data acquisition.”
Industry 4.0 and the Automotive Industry
“It takes about 30 hours to manufacture a vehicle. During that time, each car generates massive amounts of data,” points out Robert Engelhorn, director of the Munich plant. “With the help of artificial intelligence and smart data analytics, we can use this data to manage and analyze our production intelligently. AI is helping us to streamline our manufacturing even further and ensure premium quality for every customer. It also saves our employees from having to do monotonous, repetitive tasks.”
One part of the plant that is already seeing benefits from AI is the press shop, which turns more than 30,000 sheet metal blanks a day into body parts for vehicles. Each blank is given a laser code at the start of production so the body part can be clearly identified throughout the manufacturing process. This code is picked up by BMW’s iQ Press system, which records material and process parameters, such as the thickness of the metal and oil layer, and the temperature and speed of the presses. These parameters are related to the quality of the parts produced.
BMW-led study highlights need for AI-based AM part identification
With time-to-market in the automotive industry steadily decreasing, demand for prototyping components is higher than before and the vision of large-scale production, delivering just-in-time to assembly lines, is emerging. This is not only a question of increasing output quantity and production speed but also of economic viability. The process chain of current available AM technologies still includes a high amount of labor intensive work and process steps, which lead to a high proportion of personnel costs and decreased product throughput. Also, these operations lead to bottlenecks and downtimes in the overall process chain.
Fully automated end-of-line test bench for BMW eDrive
BMW Group and NVIDIA take virtual factory planning to the next level
The BMW Group and NVIDIA are generating a completely new approach to planning highly complex manufacturing systems – with the Omniverse platform. The virtual factory planning tool integrates a range of planning data and applications and allows real-time collaboration with unrestricted compatibility. As industry leaders, the BMW Group and NVIDIA are setting new standards in virtual factory planning.