What is Digital Twin technology? A quick overview!

What is a digital twin?

A digital twin is a digital representation of a physical object, person, or process, contextualized in a digital version of its environment. Digital twins can help an organization simulate real situations and their outcomes, ultimately allowing it to make better decisions.

A digital twin is a virtual replica of a physical object, person, or process that can be used to simulate its behavior to understand better how it works in real life. Digital twins are linked to real data sources from the environment, which means that the twin updates in real-time to reflect the original version. Digital twins also comprise a layer of behavioral insights and visualizations derived from data. When interconnected within one system, digital twins can form what’s known as an enterprise metaverse: a digital and often immersive environment that replicates and connects every aspect of an organization to optimize simulations, scenario planning, and decision-making.

There are a few different types of digital twins. First, there’s a product twin, which is a representation of a product. This digital twin can include products at various stages of the life cycle, from initial concept design and engineering through to full functionality—meaning you get live, real-time data on a product as if it’s in service. One great example of a product twin is something you probably already have in your pocket: Google Maps is a digital twin of the Earth’s surface. It links real-time data on traffic to help optimize your commute.

Other types of twins include production plant twins, which represent an entire manufacturing facility, or procurement and supply chain twins, also called network twins. And finally, infrastructure twins represent physical infrastructure such as a highway, a building, or even a stadium.

Digital twins have the potential to deliver more agile and resilient operations. And their potential isn’t lost on the CEO. McKinsey research indicates that 70 percent of C-suite technology executives at large enterprises are already exploring and investing in digital twins.

How do digital twins work?

Engineers extract data from many sources to create a digital twin of a physical asset. The most general approach is to attach sensors to physical products and feed the data to the digital twin. After the team collects and processes the data, they combine it with AI and ML algorithms. Once that’s done, they run it through virtual models that provide a solid testing ground for experimentation and analysis.

What is the difference between digital twins vs. simulation, you ask? Digital twins constantly exchange data between the real and the virtual. In contrast, simulations only take information from the physical one time without ever really having a back-and-forth.

What kind of value can digital twins bring to organizations?

One of the areas where digital twins can bring the most value is the reduction of time to market. Digital twins can allow for rapid iterations and optimizations of product designs—far faster than physically testing every single prototype. What’s more, digital twins can result in significant improvements in product quality. By simulating the product throughout the manufacturing process, it’s possible to identify flaws in the design much earlier.

Finally, by mirroring a product in service, it’s possible to create a single source of truth for how the design is functioning, allowing for real-time adjustment or redesign.

Examples of how digital twins have been used in manufacturing systems:

1. Bridgestone's digital twin technology: Bridgestone, a global leader in tire manufacturing, uses digital twin technology to understand the impact of various factors like driving style and speed on tire performance and durability. This allows them to advise operators on preventing breakdowns and increasing tire lifespan.
2. Siemens' digital twin for gas turbine production: When Siemens acquired Rolls-Royce's energy gas turbine business, they introduced the SGT-A65 aero-derivative gas turbine. To predict performance, forecast KPIs, and evaluate investment options, Siemens used digital twin technology to visualize the entire production and maintenance process, including supply chain logistics.
3. Anheuser-Busch InBev: A brewing and supply chain digital twin enables brewers to adjust inputs based on active conditions and can automatically compensate for production bottlenecks (for instance, when vats are full).
4. SoFi Stadium. To help optimize stadium management and operations, a digital twin aggregates multiple data sources including information about the stadium’s structure and real-time football data.
5. Space Force: This branch of the US Armed Forces is creating a digital twin of space, including replicas of extraterrestrial bodies and satellites.
6. SpaceX: A digital twin of the Space X’s Dragon capsule spacecraft enables operators to monitor and adjust trajectories, loads, and propulsion systems, intending to maximize safety and reliability during transport.
7. Emirates Team New Zealand: A digital twin of sailing environments, boats, and crew members enables Emirates Team New Zealand to test boat designs without actually building them. This has allowed the champion sailing team to evaluate thousands—rather than just hundreds—of hydrofoil designs.

These examples demonstrate how digital twins are transforming remote monitoring in manufacturing by providing real-time insights, enabling proactive maintenance, and allowing centralized control of geographically dispersed assets and processes.

An organization with a healthy digital-twin network can layer on additional technologies required to create an enterprise metaverse. A retailer could, for instance, connect the digital twin of its retail store to the digital twins of its warehouses, supply chain, call center, and more until every part of the organization has been replicated.

In summary, the key advantages of digital twins span improved efficiency, streamlined innovation, enhanced security, better decision-making, and industry-specific benefits, making them a valuable tool for organizations across diverse sectors.