Digital Twin

What is digital twin technology?

A digital twin is a virtual model of a physical object. It spans the object's lifecycle and uses real-time data sent from sensors on the object to simulate the behavior and monitor operations. Digital twins can replicate many real-world items, from single pieces of equipment in a factory to full installations, such as wind turbines and even entire cities. Digital twin technology allows you to oversee the performance of an asset, identify potential faults, and make better-informed decisions about maintenance and lifecycle.

How does a digital twin work?

A digital twin is a virtual model designed to accurately reflect a physical object. The object being studied—for example, a wind turbine—is outfitted with various sensors related to vital areas of functionality. These sensors produce data about different aspects of the physical object’s performance, such as energy output, temperature, weather conditions and more. This data is then relayed to a processing system and applied to the digital copy.

Benefits of digital twin

Digital twins offer users many benefits. Some of the following are:

Improved performance

Real-time information and insights provided by digital twins let you optimize the performance of your equipment, plant, or facilities. Issues can be dealt with as they occur, ensuring systems work at their peak and reduce downtime.

Predictive capabilities

Digital twins can offer you a complete visual and digital view of your manufacturing plant, commercial building, or facility even if it is made up of thousands of pieces of equipment. Smart sensors monitor the output of every component, flagging issues or faults as they happen.

Remote monitoring

The virtual nature of digital twins means you can remotely monitor and control facilities. Remote monitoring also means fewer people have to check on potentially dangerous industrial equipment.

Accelerated production time

You can accelerate production time on products and facilities before they exist by building digital replicas. By running scenarios, you can see how your product or facility reacts to failures and make the necessary changes before actual production.

Types of digital twin

There are several different digital twin types, which can often run side by side within the same system. While some digital twins replicate only single parts of an object, they're all critical in providing a virtual representation. The most common types of digital twins are the following.

Component twins

Component twins, or parts twins, are the digital representation of a single piece of an entire system. These are essential parts of the operation of an asset, such as a motor within a wind turbine.

Asset twins

In digital twin terminology, assets are two or more components that work together as part of a more comprehensive system. Asset twins virtually represent how the components interact and produce performance data that you can analyze to make informed decisions.

System twins

A higher level of abstraction from asset twins are system twins, or unit twins. A system twin shows how different assets work together as part of a broader system. The visibility offered by system twin technology allows you to make decisions about performance enhancements or efficiencies.

Process twins

Process twins show you the digital environment of a whole object and provide insight into how its various components, assets, and units work together. For example, a digital process twin can digitally reproduce how your entire manufacturing facility is operating, bringing together all of the components within it.

The future of digital twin

A fundamental change to existing operating models is clearly happening. A digital reinvention is occurring in asset-intensive industries that is changing operating models in a disruptive way, requiring an integrated physical plus digital view of assets, equipment, facilities and processes. Digital twins are a vital part of that realignment.

The future of digital twins is nearly limitless, due to the fact that increasing amounts of cognitive power are constantly being devoted to their use. So digital twins are constantly learning new skills and capabilities, which means they can continue to generate the insights needed to make products better and processes more efficient.

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