Perhaps it’s because of the lasting memories of the pandemic and forced isolation from friends and family, but there doesn’t seem to be much public enthusiasm for the much-hyped virtual reality offerings from Big Tech companies. Never mind that Facebook got obsessed with technology and changed its name to Meta. The average consumer didn’t seem to want to spend a lot of time wearing a cumbersome headset to live in an alternate world. Instead, it was AI that captured the imagination. Indeed, on the other hand, it is causing a lot of anxiety about security, the future of work, and indeed society itself.
but, the study A recently published paper by management consultancy Arthur D. Little suggests that it would be unwise for companies to immediately dismiss the Metaverse in order to focus on AI. To some extent, this resonates with the views of some rivals who have been claiming support for the opportunities presented by this technology for some time. But his Blue Shift Institute’s report on the industrial metaverse provides a pretty compelling explanation of how “convergence of key technologies” is leading to gradual changes in simulation capabilities. .
The report is included in the company’s latest issue. prism Titled “Strategy Simulation — The Real Potential of the Industrial Metaverse,” the magazine argues that some of the “technology blocks” that are part of the “Fourth Industrial Revolution,” or what has been known since 2015 as Industry 4.0, It points out that it has existed for a long time. For a while. These include blockchain, virtual workplaces, virtual models, simulations, digital twins, and of course AI. For example, in the aviation industry, although virtual training has become commonplace and digital design tools and other technologies have been around for some time, Industry 4.0 implementation is still not as widespread as expected a decade ago. The book says: Barriers contributing to this situation include high upfront capital costs, difficulty coordinating the required cross-functional transformation, data security and management challenges, lack of available skills, and legacy IT systems. issues such as.
This is where the convergence of key technologies identified by Arthur D. Little comes into play. For example, a digital twin is essentially a computer program that uses real-world data to create a simulation that can predict how a product or process will perform. The report’s authors, Albert Meige and Rick Eagar, have traditionally focused primarily on individual products, components, plants, or factories. However, advances in complex systems, data visualization, and AI, as well as improvements in connectivity and collaboration technologies, and increased computing power, have significantly expanded its scope. Rather than being limited to operational improvement and design support, the digital twin concept is moving toward becoming an important tool for strategic decision-making. The report points out, for example, how automaker BMW’s iFactory is implementing a complete production strategy centered around the use of digital twins across all production sites.
In fact, Meige and Eagar put digital twins at the heart of their idea of an industrial metaverse. Ultimately, they write, it “could represent a complete end-to-end industrial system, including not only physical assets but also processes, functions, resources, and organizations.” However, four key features are needed to make this happen. they are:
Connecting — Digital twins must be permanently connected to the real world through the Internet of Things for “hot” current data and through ERP systems for “cold” stored data.
computing : The ability to process very large amounts of data from real-world systems, including analysis, system modeling, pattern recognition, and simulation to enable future scenario planning.
get pregnant — Visualize both physical and non-physical data. This involves interpreting and presenting complex data in different ways to not only simulate reality but also to facilitate understanding and explain scenarios.
cooperate — Ability to enable extensive interaction between internal staff and external customers, partners, etc.
Arthur D. Little consultants suggest it could take up to five years for all the pieces of the puzzle needed to fully commercialize the concept, but business leaders I urge you to take this seriously now. He has three main reasons for this. Traditional strategic decision-making “is becoming inadequate to meet the combined challenges of complexity, acceleration, awareness, and sustainability,” in areas such as training, operations and maintenance, and collaboration. has received great benefits. And the market is likely to expand rapidly in the coming years. (Arthur D. Little says conservative estimates could reach about $400 billion by 2030, but other estimates suggest it could be more than double that.) doing.)
To make the most of this, companies should consider four steps, the report says. Without a mature digital foundation, it is not easy to jump into implementing a complete industrial metaverse, so executives need to start with a clear understanding of where their organization’s digital journey is heading. there is. Next, you need to evaluate which existing applications and usages are most likely to add the most value as you move forward. These should be developed using an agile and responsive ‘test and learn approach’, using relatively small pilot projects with short payback periods. Above all, we need to adopt a different mindset and culture that embraces the idea of sharing more data than has traditionally been shared between commercial partners. It is by developing a partner ecosystem that the true benefits of the industrial metaverse emerge, where each partner benefits in terms of faster customer response, smoother customer experience, and reduced working capital. Because you can.