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.”
Schaeffler Group's Factory simulation is part of this use case:
Automotive and industrial supplier of precision bearings and motion technology.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Helped Schaeffler deploy trained AI models onto physical robots using a virtual controller.
Related implementations across industries and use cases
Programming VW robots for roof liners took months of manual tuning. Virtual simulation cut setup time to <1 day.
Factory design was slow and siloed. Now, digital twins run thermal simulations 150x faster, validating global layouts in minutes.
Experts manually flipped through manuals to code. Technicians now use natural language to build and test programs 80% faster.
Programming VW robots for roof liners took months of manual tuning. Virtual simulation cut setup time to <1 day.
Factory design was slow and siloed. Now, digital twins run thermal simulations 150x faster, validating global layouts in minutes.
Conflicting rules across 3,000 services blocked qualified drivers. AI now traverses a graph to validate dependencies in milliseconds.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Manual translation dragged 60-minute calls to 90+, silencing experts. Now, live AI captions let teams collaborate in native languages.
Fleet repair estimates took up to 48 hours. Autonomous agents now process them in 30 minutes, absorbing a 10x volume surge.
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.”
Schaeffler Group's Factory simulation is part of this use case:
Automotive and industrial supplier of precision bearings and motion technology.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Helped Schaeffler deploy trained AI models onto physical robots using a virtual controller.
Related implementations across industries and use cases
Programming VW robots for roof liners took months of manual tuning. Virtual simulation cut setup time to <1 day.
Factory design was slow and siloed. Now, digital twins run thermal simulations 150x faster, validating global layouts in minutes.
Experts manually flipped through manuals to code. Technicians now use natural language to build and test programs 80% faster.
Programming VW robots for roof liners took months of manual tuning. Virtual simulation cut setup time to <1 day.
Factory design was slow and siloed. Now, digital twins run thermal simulations 150x faster, validating global layouts in minutes.
Conflicting rules across 3,000 services blocked qualified drivers. AI now traverses a graph to validate dependencies in milliseconds.
Sourcing native speakers for 14 markets was costly. Now, AI handles 40% of routine queries and translates live for a central English team.
Manual translation dragged 60-minute calls to 90+, silencing experts. Now, live AI captions let teams collaborate in native languages.
Fleet repair estimates took up to 48 hours. Autonomous agents now process them in 30 minutes, absorbing a 10x volume surge.