German carmaker BMW plans to begin making drivetrains for electrical automobiles at an enormous manufacturing facility in Regensburg, Bavaria, later in 2021. Well earlier than any new components roll off the manufacturing line, the complete manufacturing course of will run in stunningly practical element inside a digital model of the manufacturing facility.
The simulation permits managers to plan the manufacturing course of in better element than was beforehand attainable, says Markus Grüeneisl, who leads manufacturing technique at BMW. “We now have a perfect digital twin of our real-time production,” he says.
The simulation is a part of BMW’s plan to use extra artificial intelligence in manufacturing. Grüeneisl says machine-learning algorithms can simulate robots performing complicated maneuvers to discover the most effective course of. Over time, BMW desires to use the simulation to have robots find out how to carry out more and more complicated jobs.
BMW used a software program platform referred to as Omniverse, developed by the chipmaker Nvidia, to recreate the Regensburg manufacturing line. Last 12 months, BMW mentioned it was utilizing an AI platform from Nvidia referred to as Isaac to train robots for certain new tasks.
“In the future, I am very positive that we can just put a new robot in this facility, and say, ‘OK, talk with the other robots and find the best way to produce this body,’” Grüeneisl says.
Manufacturers have used laptop simulations to hone their meeting traces for a while. But Omniverse permits the complete manufacturing course of to be simulated with photo-realistic particulars, and with bodily properties like gravity and completely different supplies. It’s attainable to lay out the manufacturing course of from begin to end, and to see how adjustments to one half may need knock-on results on one other. It is less complicated to construct a extra complicated digital surroundings as a result of completely different 3D fashions could be imported into the system. Omniverse makes use of an open file commonplace suitable with quite a few computer-aided design packages.
The software program may also simulate avatars of human employees grabbing components and instruments, and assembling elements, to discover the finest process and reduce ergonomic issues. It may also make it attainable for fewer employees to full a selected job, Grüeneisl says.
“We do AI simulation of how people move around the factory,” says Richard Kerris, normal supervisor for Omniverse at Nvidia. He calls the challenge “one of the most complex simulations that’s ever been done.”
There’s rising curiosity in utilizing AI to management robots and different industrial machines. Encouraged by current progress in AI, some startups are centered on having robots be taught in simulation how to carry out fiendishly troublesome duties like grasping irregular objects, expertise that might ultimately assist automate a lot ecommerce and logistics work. This usually makes use of an AI strategy referred to as reinforcement learning, which entails an algorithm experimenting and studying, from constructive suggestions, how to obtain a selected purpose.
“This is definitely the way to go,” says Ding Zhao, a professor at Carnegie Mellon University who focuses on AI and digital simulations. Zhao says simulations are essential to utilizing AI for industrial purposes, partly as a result of it’s unattainable to run machines via hundreds of thousands of cycles to collect coaching information. In addition, he says, it’s necessary for machine-learning fashions to be taught by experimenting with unsafe conditions, reminiscent of two robots colliding, which can’t be completed with actual {hardware}. “Machine learning is data-hungry, and collecting it in the real world is expensive and risky,” he says.
Willy Shih, a professor at Harvard Business School who makes a speciality of manufacturing expertise, says the sophistication of simulation has been rising steadily, and he says simulation primarily saves money and time by preempting future manufacturing issues.
Shih says there’s loads of hype round AI for manufacturing however provides, “There are lots and lots of applications” for the expertise too.
Nvidia CEO Jensen Huang mentioned BMW’s use of Omniverse throughout his keynote at the firm’s annual GTC convention, held just about on Monday. Nvidia initially made graphics chips for gaming however broadened its focus when these chips proved adept at coaching AI applications. The firm has since leapt into a number of different industries the place AI is necessary, together with automotive and medical imaging.
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