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‘Lower Risk, Greater Resilience’: Cosmo Tech Vision for the Industrial Metaverse

‘Lower Risk, Greater Resilience’: Cosmo Tech Vision for the Industrial Metaverse

A lot has been written about the metaverse and the nexus between the physical and digital world in the last year, with much of that focused on the consumer metaverse. Crypto, Blockchain, AR/VR, Avatars, communication and online interactions, trading in digital goods such as NFTs and Facebook’s deep move into the space have all been written about extensively. Less attention has been paid by the press to the industrial metaverse, yet arguably it is the industrial metaverse that will have a far greater impact on our world. 

The industrial metaverse has been defined by Microsoft GM Tony Shakib as a collection of capabilities in the intelligent cloud, and on the intelligent edge, working together, that allow a company to connect physical assets and to model anything physical or logical, from simple devices or products to complex environments. Recently, Satya Nadella restated “The same paradigm shifts – the digitization of people, places and things and their interactions – are also happening in the industrial metaverse. We are helping companies optimize their operations and automate, simulate and predict every business function and process, using IoT, Digital Twins, Mesh and the HoloLens platform”. Unlike much of the consumer metaverse, the industrial metaverse is not a concept or a work in progress: it’s a reality, right now.

Cosmo Tech was invited by Natixis to speak about his vision for the industrial metaverse – here are four of the highlights from this talk.

At the Intersection of the Physical and Virtual Worlds

“What matters as well is how you forecast and how you look at your future, your financial future, your exposure to risk, and how to react – that’s where the industrial metaverse adds enormous value to business.”

 

Even if the industrial metaverse is beyond the physical environment, decision makers can never entirely ignore the physical world. Digital twins in the industrial metaverse model that physical environment, replicating it virtually in all its complexity.

Consider a wind farm, a real-world example of a complex system. There are physical elements that will need to be modeled including the windmills, machines and the wind forcast. But there are also elements of the wind farm system that are related to those physical components that are impacting operator profitability energy market prices, maintenance teams and costs, financial investments in the future of the energy generation network, and connections to the wider electrical grid, including the traceability of energy production carbon footprint.

Of course, decision makers need to be able to look at this system in the present and make choices about the here and now. But they also need to be able to look into the future and set the right course for the whole wind farm system. The industrial metaverse and the digital twins within it allows decision makers to do just that.

Digital Twins and Simulation in the Industrial Metaverse

“When you add simulation, you gain insight on the impact of any disruption and how to react to any scenario – that’s what’s new with a Prescriptive Simulation Twin. Simulation adds an axis of time, allowing you to anticipate what’s to come and make the right choices.”

 

Simulation is not a new technology or technique; it’s been a tool that decision makers have leant on for decades. However, the capacity to simulate the past, present, and the future across the system is cutting-edge. Deploying that simulation capacity to the industrial metaverse is a means to generate insights that can guide planning efforts to profitability and sustainability.

Digital twins are a more recent technology than simulation but, until recently, they could only offer insights about the past or the present. Combining advanced simulation with digital twins in the shape of a Prescriptive Simulation Twin is an enormously powerful tool in the industrial metaverse.

Digital twins without simulation only represent a single virtual copy of the real world, and are not able to clone and modify those virtual worlds to test scenarios. 

With a Prescriptive Simulation Twin, decision makers unlock not only the past and present but the future, too. They have a chance to simulate current strategies in place as well as strategies to exploit every possible future. There are incredible cost savings to realize and operational efficiencies waiting to be unlocked.

Prescriptive Simulation Twins and Sustainability in the Industrial Metaverse

“Nexans has announced they plan to be carbon neutral in 2030 and will achieve this thanks to the help of Prescriptive Simulation Twins.”

 

Sustainability is increasingly a key concern for decision makers in industry. Thanks to Prescriptive Simulation Twins in the industrial metaverse, they can now set the right course with confidence to achieve a sustainable future. 

Nexans is a good example of how to leverage a Prescriptive Simulation Twin in the industrial metaverse to cement sustainable operational practices and achieve broad environmental goals. The company has set a deadline of 2030 to achieve carbon neutrality across its entire global operations. Nexans executives understand that achieving this goal means minimizing carbon emissions not only in their own business but across their entire supply chain and for their downstream partners.

Prescriptive Simulation Twins are helping Nexans to take control of their sustainability strategy and understand the impact of every decision on the future of their business, before any of those decisions are made. Taking advantage of the power of the industrial metaverse means Nexans can maintain profitability and competitiveness while meeting their sustainability goals on schedule.

Accelerating the Adoption of Prescriptive Simulation Twins in the Industrial Metaverse

“Digital twins in the industrial metaverse can be large in scope but companies can realize real value and a quick ROI by starting incrementally.”

Early adopters of digital twins and other tools in the industrial metaverse are already achieving great success. However, there is significant scope to accelerate the adoption of these new technologies in two ways.

First, companies can begin with small, finely targeted digital twin deployments. These digital twins can be focused on solving a specific problem rapidly, returning value to the company quickly and with the potential to expand across the organization.

Second, experts in digital twins and the industrial metaverse can continue to educate the market on the possibilities that Prescriptive Simulation Twins offer decision makers. They can show the value that is generated, talk about the industry leaders using the technology to full effect, and point to the quantitative and qualitative results they are achieving thanks to simulation in the industrial metaverse.

As adoption of Prescriptive Simulation Twins in the industrial metaverse advances and the results that early adopters already achieve become more common, the benefits to all stakeholders in terms of efficiency, profitability, and sustainability will only accelerate further.

Conclusion

Digital twins are an essential element on the industrial metaverse landscape, but digital twins with the capacity to simulate complex systems – and therefore having the capacity to predict, anticipate, and generate effective operational and strategic plans – are the truly game-changing technology of that metaverse.

This industrial metaverse is not about crypto, avatars and interpersonal communication over social networks; instead, it is about better anticipating the future, developing optimal plans, and executing those plans in complex, uncertain environments profitably and sustainably. As Blockchain is the key technology enabler for Crypto and more generally the consumer metaverse, the key technology enablers of the Industrial Metaverse are:

  • Deep Modeling of connected systems to simulate future states, including entities, interactions, hierarchies, dynamics to monitor, anticipate any situation and automatically mitigate the impact of disruptions.
  • Virtually test real-world scenarios with specialized data workflow management for the business-as-usual baseline, what-if alternative, and synthetic outputs, while providing full traceability and transparency.
  • Orchestrate simulation and analytics computing at scale including connecting various connected engines at scale, experiment libraries for optimization, uncertainty analysis and automation based on synthetic data-based machine learning and RL Brain teaching.

See all of Cosmo Tech’s talk on the industrial metaverse below.

Watch the replay

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