AI-Enabled Digital Twins Enhance Productiveness, Sustainability


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Digital twins aren’t a brand new instrument for the chip business, however they’re getting democratized to some extent the place they’re extra accessible for a broader set of economic functions.

The flexibility to ingest extra, higher-quality knowledge from a wider array of sources and the appliance of synthetic intelligence helps to lengthen digital twins past product design to nearly envision manufacturing environments, which is able to cut back waste in addition to contribute to assembly sustainability targets. And because the chip business ramps up U.S. onshore manufacturing within the wake of the CHIPS Act, digital twins are poised to be a essential instrument for workforce growth whereas additionally accelerating productiveness.

In early February 2024, the Nationwide Institute of Requirements and Know-how (NIST) introduced its intent to create a brand new semiconductor manufacturing institute that can use digital twin expertise for manufacturing, packaging and meeting. NIST is seeking to corral curriculum and finest practices via its CHIPS Analysis and Growth Workplace to launch a contest for a brand new public-private Manufacturing USA Institute.

Michael Grieves, government director of the Digital Twin Institute, pioneered the idea of digital twins in 2002. He proposed the digital twin because the conceptual mannequin underlying product lifecycle administration with a special title—it was NASA’s John Vickers who wrote “digital twins” into the company’s roadmap in 2010.

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Grieves preferred that time period higher, he advised EE Instances in an interview, and about 5 years later, computing capabilities allowed the adoption of digital twins to hit exponential development as use instances in manufacturing had been recognized, he stated. “We began to see the entire concept of with the ability to use info to exchange wasted assets as a price driver for digital twins.”

Digital twins are more practical when silos of data are eradicated, Grieves added. “Relying on what practical space they had been in, you wound up with large inefficiencies or the shortcoming to optimize your complete course of.”

Increasing using digital twins out to manufacturing amenities is the pure evolution of the digital strategy the chip business has used for many years, Michael Munsey, VP of semiconductors at Siemens, advised EE Instances in an unique interview. “The idea of a digital twin, despite the fact that we could not have referred to as it a digital twin, has been core to the semiconductor business for a really, very very long time.”

Digital twins are being prolonged to visualise tools and manufacturing amenities earlier than they’re constructed, then optimized as soon as they’re in manufacturing. (Supply: Siemens)

Optimizing manufacturing amenities for sustainability

Munsey stated digital twins can be utilized to construct something, so why not the manufacturing amenities that produce semiconductors—not simply the units themselves? “You possibly can truly construct a digital illustration and simulate it and optimize it lengthy earlier than you ever construct the bodily factor,” he stated.

Constructing a digital twin of a fab permits for the modeling of the manufacturing of the chip, making it attainable to optimize a facility earlier than concrete is ever poured, Munsey stated.

A digital twin does greater than simulate the manufacturing course of, he added. It additionally optimizes all of the electrical energy, water and chemical substances getting used, which helps to realize sustainability targets. Combine in internet-of-things sensors from an precise manufacturing atmosphere, he stated, and you’ll herald real-time knowledge again to the digital twin to check additional optimizations.

Munsey defined it’s now attainable to have an entire, closed loop the place manufacturing knowledge might be taken again all the way in which to the early design stage to enhance processes, methodologies and choices.

Lam Analysis’s imaginative and prescient for digital twins is that they’re a full illustration of all semiconductor manufacturing methods and processes, David Fried, company VP of the corporate’s Semiverse Options, advised EE Instances in an unique interview. “A fancy system could even have many layers of digital twins, every containing the related and required knowledge to realize a particular goal.”

Constructing an entire, holistic image

Lam is concerned within the creation of digital twins in 4 key areas, Fried stated, together with the gadget scale for detailed built-in modeling of a tool to scale back cycles of silicon studying, in addition to the method scale through the use of simulation to streamline course of growth.

On the reactor scale, he defined, digital twins can simulate operation circumstances within the chamber to foretell and optimize course of behaviors, whereas tools and experience might be constructed quicker and extra successfully and cut back instrument downtime with AI-enabled troubleshooting.

Because the semiconductor business drives towards net-zero transition, Fried stated Lam and its prospects are searching for good methods to realize extra whereas utilizing much less supplies and vitality. Extending the bodily infrastructure into the digital world with digital twins might help to scale back the consumption of bodily supplies, fuel and water, he stated.

Gear-scale twins are additionally essential instruments in coaching the service engineering workforce. Up to now, this coaching needed to be finished at a bodily website, however couldn’t start till a brand new instrument was constructed, shipped and put in. Lam’s technical coaching facilities—situated around the globe—are geared up with virtual-reality methods to permit for simpler entry to coaching on new instruments and nearer proximity to prospects.

Jerry Chen, head of worldwide enterprise growth within the industrials and manufacturing sector at Nvidia, advised EE Instances in an unique interview that using digital twins has been considerably democratized far past simply getting used for giant, advanced and mission-critical methods like spacecraft and different aerospace methods.

Higher knowledge, AI increase digital twin functionality

Extra not too long ago, Chen stated, digital twins have been capable of benefit from extra refined AI fashions, which permits them to be extra correct and permit for extra experimentation. “Not solely are you able to do extra of them with out expending the infrastructure and the fabric consumption to do these experiments, however you may as well do them at super-real time,” he stated.

Eric Brecken, director of expertise coverage for Nvidia’s authorities affairs workforce, stated elevated entry to knowledge has been accompanied by improved interoperability between methods, which has been pushed by AI functions with options that translate textual content into picture, speech and video. “Dissimilar knowledge can now transfer extra seamlessly between layers,” he stated.

That is particularly useful for the semiconductor business as a result of there are a lot of layers that require complete simulations, Brecken stated. “It requires quite a lot of knowledge handoffs at very completely different layers.” The democratization of digital twins means there are alternatives to share finest practices in an open-source mannequin, he added.

Chen stated constructing off a standard expertise platform to share knowledge might cut back marginal prices for the ecosystem by sharing knowledge in a safe approach throughout all of the disparate subsystems that they’re all creating these fashions for. “We’ve got been on this journey now for constructing connective applied sciences for digital twins,” he stated.

Generic, shared fashions enhance business productiveness

Nvidia’s Omniverse platform has been largely targeted on the manufacturing unit degree, Chen stated, “however more and more, we’re seeing that extending to different areas within the layer cake as properly.” The intention isn’t to create a singular answer for the market, he defined, however to construct out a platform of enabling applied sciences to permit the ecosystems to construct up and join and talk between the disparate artificial fashions.

Chen stated AI has been a game-changer for digital twins in that it aids the event of basis fashions which can be comparatively generic that may be added to with domain-specific and proprietary info.

Platforms like Nvidia’s Omniverse platform are being prolonged throughout numerous layers to permit the ecosystems to construct up and join and talk between the disparate artificial fashions that benefit from the various sources out there. (Supply: Nvidia)

Elevated accessibility of digital twins can enhance productiveness, which is why their use is being mentioned in relation to workforce growth efforts associated to the CHIPS Act.

Lam’s Fried stated expertise scarcity confronted by the chip business is placing calls for on training that seem daunting. “It’s cost-prohibitive for educational establishments to offer bodily entry to essentially the most superior nanotechnologies.”

Lam added that experimenting with unstable chemistries essential within the growth and creation of semiconductors might be harmful for college students who’re studying to work with semiconductor manufacturing tools. “Nearly simulating real-world labs gives higher democratization of engineering expertise coaching, heightened security, improved sustainability and higher entry to new expertise swimming pools around the globe,” he stated.

Grieves stated the most important good thing about digital twins augmented by AI is the present of time. AI might be set unfastened to strive completely different mixtures and provide you with options that people don’t have the bandwidth for, permitting for extra innovation and shortened timelines—which aligns with the targets of the CHIPS Act. “Essentially the most worthwhile useful resource we’ve are the ticks of the clock,” he stated.


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