BMW collaborates with Nvidia on virtual factory planning

The BMW Group and Nvidia are collaborating to develop a new approach to planning highly complex manufacturing systems.

The BMW Group and Nvidia are generating a completely new approach to planning highly complex manufacturing systems with a new virtual factory planning tool.

Called the ‘Omniverse platform’, the new tool integrates a range of planning data and applications and allows real-time collaboration with unrestricted compatibility.


Virtual factory planning is already widespread, but until now it has required data to be imported from various applications. This is not only time-consuming but also raises compatibility issues. In addition, the data is not always up to date.

In the future, the Omniverse platform will enable live data to be collected and collated from all the relevant databases to create a joint simulation, eliminating the need to reimport data. This will allow planners and production specialists to plan highly complex production systems even more quickly and accurately, without interface losses or compatibility problems.

The Omniverse platform can integrate data from various professional design and planning tools from a range of different producers and uses it to generate photo-realistic real-time simulations in a single collaborative setting.

Outstanding photorealistic quality is just one of the many benefits of Omniverse. Another is that employees at different sites in different time zones can access the virtual simulation and work together to plan and optimise details of a process or production system whenever they need to.

In the future, planners and production specialists will collaborate using real-time data that is synchronised in the Omniverse cloud infrastructure. They will also be able to discuss the integration of new production systems with suppliers.

Production planners at the BMW Group will be able to visualise the entire planning lifecycle for every plant in the global production network, accelerated by scalable GPU performance. This will be supported by a wide range of AI-capable application cases, from autonomous robotics to predictive maintenance and data analysis.