Programming robots took hundreds of hours. Using digital twins, engineers now train precise tasks in half a day.
A global motion technology manufacturer operating over 100 plants produces complex components for the automotive and industrial sectors.
Labor shortages and rising product complexity strained operations, while developing new robotic tasks for assembly lines required hundreds of hours...
“Schaeffler is consistently and persistently driving the digitalization of its plants. To be able to shape the production of the future, you need strong partners like NVIDIA. Together, we will create a digital ecosystem for our more than 100 plants that will sustainably revolutionize production processes.”
Automotive and industrial supplier of precision bearings and motion technology.
Helped Schaeffler deploy trained AI models onto physical robots using a virtual controller.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Schaeffler Group's Factory simulation is part of this use case:
Related implementations across industries and use cases
Data silos blocked real-world simulation. Now, teams validate site physics and safety risks on a unified digital twin.
Data silos at 120 sites blocked scaling. A unified cloud now runs 1,200+ AI apps, automating quality checks and cutting energy costs 12%.
Engineers waited weeks for physical hardware to test code. Virtual units now enable immediate validation, cutting cycles to hours.
Data silos blocked real-world simulation. Now, teams validate site physics and safety risks on a unified digital twin.
Manual estimates risked $300k units not fitting. Teams now simulate layouts in a digital twin, verifying fit before physical install.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Manual underwriting and billing created operational bottlenecks. AI now automates submissions and policy checks, freeing brokers for advisory work.
Programming robots took hundreds of hours. Using digital twins, engineers now train precise tasks in half a day.
A global motion technology manufacturer operating over 100 plants produces complex components for the automotive and industrial sectors.
Labor shortages and rising product complexity strained operations, while developing new robotic tasks for assembly lines required hundreds of hours...
“Schaeffler is consistently and persistently driving the digitalization of its plants. To be able to shape the production of the future, you need strong partners like NVIDIA. Together, we will create a digital ecosystem for our more than 100 plants that will sustainably revolutionize production processes.”
Automotive and industrial supplier of precision bearings and motion technology.
Helped Schaeffler deploy trained AI models onto physical robots using a virtual controller.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Schaeffler Group's Factory simulation is part of this use case:
Related implementations across industries and use cases
Data silos blocked real-world simulation. Now, teams validate site physics and safety risks on a unified digital twin.
Data silos at 120 sites blocked scaling. A unified cloud now runs 1,200+ AI apps, automating quality checks and cutting energy costs 12%.
Engineers waited weeks for physical hardware to test code. Virtual units now enable immediate validation, cutting cycles to hours.
Data silos blocked real-world simulation. Now, teams validate site physics and safety risks on a unified digital twin.
Manual estimates risked $300k units not fitting. Teams now simulate layouts in a digital twin, verifying fit before physical install.
Manual reviews and language gaps dragged repairs to a week. AI now diagnoses faults in 100 languages, halving the cycle.
Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Manual underwriting and billing created operational bottlenecks. AI now automates submissions and policy checks, freeing brokers for advisory work.