What is a
digital twin?

Businesses investigating ways to optimize their products and systems may find determining the right changes to make can be costly and time-consuming. It can be challenging to generate an accurate assessment without access to near real-time data from a wide range of inputs. This is where the concept of digital twinning can be so critical, as it can help organizations create accurate and responsive models to provide powerful insights into their operations.

A digital twin is a virtual representation or model of a physical object or system that can be used to test how the physical twin will respond in a particular situation. Because the digital twin "lives" in a virtual environment, you can make changes to the model as well as surrounding processes to see how it reacts. For example, you can test a new machine in the virtual model of your manufacturing floor to see the impact on productivity and determine if the ROI is worth the cost. Once you purchase the machine, you can make adjustments to other machines on the floor as well as the processes based on data gathered from the modeling.

The use of digital twins is expected to grow significantly in the near future—MarketsandMarkets predicts the market will grow 60.6% annually to be worth $73.5 billion by 2027.

The idea of digital twinning should not be confused with creating simulations. The key difference is one of scale. Simulations typically focus on a specific process, such as the air conditioning flow of a building. Digital twins include models of multiple systems and processes, such as all of the equipment that operates an entire building. Simulations also often do not use near real-time data, whereas with a digital twin, you can create a virtual environment that provides a more realistic setting and more relevant data.

Digital twins require Internet of Things (IoT) sensors to collect data from connected devices about the physical performance of the relevant object or system. This data is then processed so it can be used to build a virtual copy of the object or system. Once built, a digital model can run simulations to generate insights into performance, which can then be applied to the physical twin.

Within the overarching concept of digital twins, organizations can select between multiple types when creating their virtual environment. Common ways you can use digital twin technology include:

• Component digital twins: This type of twin represents a single part of a larger system. For example, a component can evaluate and monitor the braking system for autonomous cars.
• System digital twins: Multiple component twins work together to create a system digital twin, such as a braking system twin working with the steering component twin and the engine twin to create the autonomous vehicle system twin.
• Process digital twins: By creating a model of a workflow or process, you can spot areas for improvement to make the process more efficient or save money. For example, a retail organization can use this type for its supply chain management to gain data and perform modeling to spot inefficiencies and potential pitfalls.
• Human digital twins: Healthcare workers can use the technology to create virtual versions of human patients to help proactively treat patients. Additionally, human digital twins provide a realistic training opportunity with immediate feedback.
• Organizational digital twin: By using digital twinning to mirror an entire business, you can see how all of the resources and departments work together. Leaders can see how changing different processes and policies can impact the overall business. Organizational digital twins also can help businesses considering a company acquisition gain a realistic view of the operations. Additionally, digital twins can make the merger process less painful by allowing for testing different scenarios.

Digital twins can be used in any industry, however, there are some sectors where the technology has been more widely adopted. Example digital twin use cases include:

Production processes can be complex, involving many pieces of equipment, different processes and numerous human resources. Digital twin technology can help manufacturers optimize the entire process from start to finish to improve quality, increase efficiency and save money. The technology can also help predict equipment issues and proactively provide maintenance, which can prevent costly downtime. In the supply chain companies can seek out efficiency improvements by using digital twins for optimizing the supply chain process. Digital twins allow a company to spot potential weak links as well as repetitive processes.

By using human digital twins, healthcare providers and researchers can test new treatments as well as spot early signs of illness. The data collected can help providers determine the best treatment for specific patients. Additionally, healthcare systems can use digital twins to aid with planning and assessing designs and workflows for new and existing healthcare facility spaces. Before a health system ever breaks ground on a new hospital, digital twinning can provide a comprehensive 3D picture of historic and future scenarios, while also creating organizational digital twins to help assess and improve operations and processes.

Building and maintaining power plants and wind turbines can be exceptionally time-consuming and costly. Using digital twins can help organizations compare different plant optimization alternatives to help create the most efficient system.

There are several benefits that could be realized by adopting digital twinning technology, such as:

Instead of making expensive changes in implementation after deployment or even making poor purchasing decisions, digital twins can help companies make the best decision before committing to a physical design. Additionally, companies can reduce unplanned downtime and are able to conduct preventive maintenance, which may reduce costly repairs. For example, GE Digital estimates that digital twin technology can reduce reactive maintenance by 40% in less than a year. The company also estimates its customers have saved billions in lower operations and maintenance costs. Similarly, Deloitte estimates cost savings of 70-80% for digital twin users.

Similarly, improved planning through digital twin technology can be used at a larger scale such as in the design of cities. ABI Research expects cities to achieve cost savings of $280 billion by 2030 through the use of digital twins for more efficient urban planning.

By simulating potential situations, organizations can help prevent safety issues before they happen. For example, if the digital twin shows that a specific machine setup on a manufacturing plant floor increases the potential for falls, then the company can redesign the placement, preventing accidents.

Digital twins allow manufacturing companies to optimize their efficiency, helping to get products to market more quickly. GE Digital estimates that the use of digital twins can help industrial companies—including manufacturers—achieve outcomes in 75% less time.