In the tech industry, “digital twin” has replaced “metaverse” as the new buzzword, which in my opinion is a good thing. The big difference between the term “Metaverse” and “digital twin” is that digital twins are always built for a specific purpose. You won’t deal with any vague statements like, “digital twins will change everything.” The key to understanding digital twins is defining how they will be used, but first let’s get a general definition of what a digital twin is.
Simply, a digital twin is a virtual representation of a physical object. The power of a digital twin comes from the fact that the model can be enhanced with outside data. The virtual model often will be used for simulations to help make decisions about the real object. In layman's terms, this is basically a 3D simulation that allows you to gain a deeper understanding of how the real object will function. If you don’t want to risk building an expensive and inefficient factory, make a digital twin of the factory first, input data on how you think that factory will function and then analyze the model to identify the potential roadblocks and challenges. This could ultimately result in substantial savings of both time and money. BMW recently stated that they expect to reduce production planning time by 30% through the use of digital twins for factory planning.
Now some people might be thinking, “This doesn’t sound like new technology, why is the term popular now?” This is largely because of the recent and dramatic increase in Artificial Intelligence (AI) capabilities, as digital twin models need to be populated with accurate AI information. While in the past, it was technically feasible to manually input this kind of information, it was often not cost-effective. The recent advances in AI allow significant new and innovative ways to populate digital twins with live data and that is why digital twins are moving up the technology priority list.
There are many examples of how digital twin technology is being used in various industries to improve performance and efficiency. Some examples include:
While there are a lot of exciting possibilities for digital twins, a word to the wise, there are also potential pitfalls. Creating and maintaining digital twin solutions can be complex, especially when integrating with other systems and data sources. The accuracy of digital twin models depends on the quality of data that is fed into them. Combine that with some ethical and legal considerations and you have a lot of factors to take into consideration when creating a high-quality digital twin.
The good news is, our industry is already considering these challenges. As companies look to start utilizing digital twin technology, those of us who are building digital solutions are already guiding people in the right direction. As AI, VR and AR become more powerful, so does the digital twin. We will soon see the true power of digital twin technology – the ability to use immersive tools, combined with AI to gain a much deeper insight into how a physical system will function. We will soon experience simulations that are truly immersive, with levels of detail we never thought were possible.
The Glimpse Group is a Virtual Reality & Augmented Reality Platform Company Comprised of Multiple Software & Services Subsidiaries Creating Innovative VR/AR Solutions (products, software, and consulting services)