Meta-universes have become one of the hottest topics in technology, favored by a wide range of fields from gaming to high-value design, engineering and manufacturing.
Many companies have already begun working to create and utilize these services to enable digital transformation in their respective fields; for example, Adobe recently announced collaborations with Coca-Cola, NASCAR, Epic Games, and NVIDIA on a range of metaverse-related projects.
Manufacturing is no exception, having pioneered one of the pillars of the metaverse: the digital twin. The digital twin represents the convergence of digital technologies such as artificial intelligence, machine learning and the Internet of Things. With all of these tightly intertwined in the meta-universe, we look forward to the rapid and exciting performance of advanced digital twin approaches that will enable the convergence of the physical and virtual.
Digital transformation in manufacturing is growing as new technologies and processes bring enhanced customer value and enablers. Nine out of ten manufacturers believe that data from connected machines and people will help with decision making and reduce costs. At the heart of driving progress is not only introducing better tools, but also ensuring that teams are able to utilize these new technologies to facilitate better understanding, collection, storage, and connectivity of data.
The Metaverse Unleashes Its Full Potential
After all, the backbone technologies of digital transformation - IoT, AI and machine learning - have been at our fingertips for years, but I believe their full potential can only be realized when we integrate them into the meta-universe, as projected market growth overshadows the painstaking efforts manufacturers have made so far to integrate these tools. These obstacles reportedly include finding skilled labor, legacy IT resources, and creating and using good (enough) data.
The digital twin is the key to overcoming these challenges and is a core component of the manufacturing meta-universe.
Essentially, digital twins bring realism to the digital world, combining virtual manufacturing simulations with real-life learning, for example, to help determine the best materials and manufacturing processes to optimize the cost and environmental impact of a product. Feeding data collected by the system on a range of issues into connected workflows - especially those augmented by AI insights - means that knowledge learned from production, defects, or product use can be used to improve future part design and help many different types of teams and skill sets to access that knowledge.
A revolution
A revolution is taking place in the field, with engineers able to augment physical-world design and testing with the digital twin's ability to provide insights into the "what-if" characteristics and behavior of products. Scaling this meta-universe approach across teams will allow engineers with different backgrounds of expertise to work together to explore complex "what-if" scenarios.
For example, "If I change the body of this car from steel to carbon composite, how much lighter will it be, and is it still safe?" Or, "If I change the shape of this jet engine blade, how much fuel can we save?" While these may seem like simple input-output questions, they have traditionally involved many different siloed actors, solutions, and experts, and a digital twin embedded in the metaverse will help bring together and answer these questions.
Think of it as the dashboard of a jet fighter, showing pilots real-time data about the aircraft's performance and alerting them when something might go wrong, or a Google Glass-style augmented reality system that provides predictive maintenance alerts when a machine is about to fail. It would be able to inform about quality issues with specific parts and recommend the best process, the most appropriate engineering department, and the best materials and robots to fix the problem.
Another example is the ability of Metaverse to become one of the pillars of sustainable manufacturing and achieve net zero growth. Today, most companies are under pressure to operate in a more sustainable way, and manufacturing has more obstacles to overcome than most. A digital twin will allow design and testing to be done holistically, learning from the physical product and optimizing future designs specifically for sustainability, while minimizing the impact on other factors such as profitability.
If manufacturing teams embrace and build a meta-universe that works for them, they will be more productive because they can easily access more and better information. In order to keep up with the latest digital developments and, more importantly, to ensure that the output is the best it can be, manufacturers need to embrace everything that the metaverse has to offer. As they say, the possibilities are endless.