Digital Twin technology is maturing; digital twins are assigned new tasks; they are deployed in more and more industries, and are moving outside the realm of their original applications. From its humble origins in product development in automotive, aerospace, and defense, digital twins have become a common analysis tool in architecture, engineering, construction, procurement, or city planning projects and even the decision-making processes for buying/selling, commissioning, and operations management. A digital twin is a model of a physical object in the digital realm, allowing developers to analyze it as a reference even if the product does not exist yet. Initially, digital twins were mainly used for low-cost prototyping, but now they are being used for various operational streamlining purposes.
A digital twin is a virtual model that accurately describes a physical object. The physical object has various IoT sensors. Data generated by the physical object – a combustion engine for example – such as power, torque, fuel consumption, and the temperature at various locations in the engine, can be relayed to the digital twin to create a real-time digital copy. Once the virtual model has collected a complete dataset, the model can be used to run simulations, analyze performance issues, and study possible improvements, which after the tests have been completed, can then be used to adjust and improve the original real-world object.
The difference between a simulation and a digital twin is that a simulation refers to replicating one process, whereas a digital twin can replicate multiple processes at once. By using a virtual model to study relevant data, an analyst can learn real-time insights about the project to make quick improvements.
Digital twins have the capability of bringing together several insights at once to make a process more efficient. They serve as a much more powerful resource than what a single simulation generates because they provide data from various vantage points. It’s possible to use this data-rich system to make a more cohesive and competitive product based on analyzing digital manipulations to the 3D version of a prototype.
According to IBM, the original concept behind digital twin technology began in 1991 with the book by Yale professor David Gelernter called Mirror Worlds: or the Day Software Puts the Universe in a Shoebox. How It Will Happen and What It Will Mean. The book explained how reality can be manipulated with the help of a computer. It was an early look into the idea of exploring the world via software without leaving home.
The first scientist to announce the application of digital twins to manufacturing in 2002 was Dr. Michael Grieves at the University of Michigan. Then in 2010 the term “digital twin” was coined by John Vickers of NASA, the aerospace agency that introduced the basic concept during space missions of the 1960s.
One of the leading AI companies of the past decade to capitalize on digital twins has been tech giant Nvidia, which has contributed to improving Pixar’s Universal Scene Description (USD) format. Nvidia is further planning on using USD for advancements in medicine and other industries. It’s also playing a role in creating virtual tools for the metaverse. Since its launch in 1993, the company has grown to be a leader in video games and graphic-based supercomputing.
Construction has been a rapidly-evolving industry due to the adoption of digital twins, particularly generative AI. Virtual technology is helping builders identify cracks in concrete more swiftly so that they can apply sealant and more durable solutions. It’s leading to conditions for allowing more open-source and customized development at worksites. The flip side of the coin is that generating 3D images using OpenAI technology raises questions as to who owns the rights to such images.
Many of today’s business leaders now predict digital twin technology will become a game-changer in 2023. It might even help alleviate supply chain disruptions that have contributed to high inflation.
Digital twins have evolved over the past few decades to include various types for different purposes. To show the versatility of the digital twin approach, here are some of the most common types:
A wide range of industries now views the use of digital twins as necessary for gaining a competitive edge in the market. Large operations that serve many people such as hospitals and banks have particularly benefited from digital twin strategies. Contact us at IoT Marketing for more information on using virtual technology to expand your business capabilities.