Digital Twin: Transforming How We Make Sense of Data

Learn why digital twin is a strategic imperative for digital transformation

What is a digital twin?

A digital twin is a virtual representation of a physical product, process, person, or place that can understand and measure its physical counterparts.

A digital twin has three components: a digital definition of its counterpart (generated from CAD, PLM, etc.), operational/experiential data of its counterpart (gathered from Internet of Things data, real-world telemetry, and beyond), and an information model (dashboards, HMIs, and more) that correlates and presents the data to drive decision making.

A digital twin is much more than a simulation, which is merely a data-driven prediction for how a physical environment/process/person/product will behave. A digital twin spans the full product lifecycle and has engineering, manufacturing, and service use cases.

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Why is a digital twin important?

With continued advances in digital technology, digital twins are becoming more robust—and more important to enterprise companies. With digital twin technology, companies can use real-world product data to inform improvements to the next generation of product, identify bottlenecks in processes with more ease, or support service technicians in the field leading to faster repair. When looking at use cases for digital twins, consider the ROI and value they will bring to the business.

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What are some challenges the digital twin helps solve?

Downtime reduction: Downtime, planned or unplanned, can cost a company significant money. With digital twin technology, businesses can be better prepared to solve issues faster, or avoid them altogether.

Operational efficiency: Digital twins can expose previously undetectable issues and guide managers to make data-driven improvements.

Product improvements: Product designers can use the insights from digital twins to improve the product in future iterations or uncover opportunities for new product lines or features based on product usage data.

Improve customer experience: Digital twins can be used to deliver novel experiences and features to customers.

Optimize service capabilities: Support service technicians and customers with guidance via augmented reality to deliver remote expert service or improve first-time fix rates.

Consistent product quality: Because digital twins have a physical counterpart, operators can see detailed data and insights, find patterns, and resolve quality or service issues proactively.

What are the benefits of digital twin technology?

Enhance supply chain agility and resilience 

Supply chain disruptions have put a spotlight on agility and resilience. A combination of emerging technologies and platforms have made it possible to pursue a digital twin of the physical end-to-end supply chain. With this type of digital twin, companies get visibility into their supply chain, such as lead times, and can make real-time adjustments internally and with their partners.

Reduce product time to market

With digital twins, companies receive continuous insights into how their products are performing in the field. With these insights, they can iterate and innovate products faster and with more efficiency.

Enable new business models (i.e., product as a service)

Digital twins sometimes have a secondary benefit if you’re able to think about the possibilities. With more data visibility into products, there could be opportunities for subscriptions and offerings that deliver enhanced service or support to customers.

Increase customer satisfaction 

Digital twins can support improved customer satisfaction though use cases like predictive maintenance, but because they collect real-time data on the product, they can also enable smoother customer service and repair operations, while informing future product improvements.

Improve product quality

This benefit comes with time and data collection through digital twins. After initial investments have been made, generational improvements of a product—based on real-world operational data from many digital twins—can inform engineers and designers when developing a new product or version.

Drive operational efficiency

Digital twins offer the insights necessary to gain those operational efficiencies across the value chain. With process-based digital twins, for example, organizations can bring together different data sets to capture real-time information on asset and production performance. Not only can they see where there might be bottlenecks, but also how potential solutions could impact the overall process.

Improve productivity

The challenge of employee turnover and retention is nearly universal across industries. When a skilled employee leaves, they almost always take their knowledge with them, creating a barrier that slows productivity. With digital twins, organizations can mitigate some of these challenges through remote monitoring and assistance.

Inform sustainability efforts

There are opportunities across the value chain to identify sustainability opportunities with digital twins. It can mean swapping out product materials for more sustainable options, reducing carbon emissions or scrap in the manufacturing process, or decreasing the number of service truck rolls.

Increase data visibility

Digital twins can break down data silos across the enterprise and unlock value across the product (or process) lifecycle. Historical data and real-time data all live in one place.

Types of digital twins

Product

Captures product lifecycle from origin through operating in customer's end environment and decommissioning.

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Process

Representations of manufacturing operations and production activities to create products and services.

People

Deliver task information to workers and/or capture data to improve process efficiency.

Places

Virtualize a place—like a factory or workstation—to gain insight into the complex workings within the environment and engage with it.

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What can digital twin do?

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Digital twins to improve service and uptime

With PTC as a partner, Howden is using technologies like augmented reality and IoT to demonstrate the power of immersive experiences. One of Howden’s goals is to use digital twin technology to reduce business risk for their customers by improving the uptime of deployed products.

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Digital twin of place, process, and people

The emerging technologies of spatial computing and analytics are enabling a digital twin of place. With both a bird’s eye and detailed view of a factory floor enabled by integrating multiple sets of data, spatial analysis offers visibility into movements within a space, and can make data-driven recommendations on how to improve processes and performance. See how it works in this video from the PTC Reality Lab.

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Dive deeper with digital twins

As industrial enterprises generate increasing volumes of data about the physical world, they are mapping this data back to the IT systems that define their products, processes, people, and places to enhance the digital thread. Digital twins are quickly proving to be a key strategic accelerator for digital transformation and the means in which to unlock the value of data across the enterprise.

In the State of Digital Twin 2022, we explore how digital twins are impacting businesses today across engineering, manufacturing, and service. While noting a digital twin strategy does come with specific challenges, we outline the potential significant benefits of the initiative.

Industry applications of digital twins

Applications with digital twins are still emerging. With the technology comes the capability for real-time feedback—and even predictive monitoring and insights. This has the potential to expose new revenue opportunities such as enhanced service delivery. The outcomes of these use cases are increased customer satisfaction and loyalty, driven by improved asset uptime and faster time-to-resolution.


As we examine all the opportunities for PTC and our customers, there are three distinct areas where digital twins will make a difference: engineering, manufacturing, and maintenance and service. Explore each area in more detail below.

Engineering

In engineering, digital twin technology provides a product lens that enables teams to better understand how products are being used in the field, and then use that data to build better products. Through this closed-loop design process, engineering organizations optimize product form, fit, and function, as well as quality far beyond what can be achieved when relying on static specification documents.

Leveraging a digital model and simulation tools, digital twins can validate performance well before—and in some cases in lieu of—physical prototyping, reducing costly late-stage redesign, and accelerating time to market.

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Manufacturing

Digital twin applications for manufacturing continue to grow, benefiting all levels of manufacturing operations. Particularly with process-based digital twins, businesses gain production visibility and planning, which improves operational agility, increases throughput, and optimizes process efficiency throughout the supply chain.

Specific use cases include production monitoring, asset monitoring and machine diagnostics, supporting visual work instructions, predictive maintenance, shop floor performance improvement, process optimization, and more.

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Service

To support maintenance and service teams, digital twins are being used to enhance service delivery and offerings that improve customer satisfaction through increased uptime and faster time to resolution. Teams are leveraging it for service parts identification and fulfillment, visual procedure guidance/verification for frontline workers, remote monitoring, and predictive service and maintenance.

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Future of digital twin technology

New technologies are emerging that will enable high-fidelity digital twins, as well as connections to transformative manufacturing processes, from generative design to additive manufacturing. Digital twins, when combined with artificial intelligence capabilities, such as machine learning and deep learning algorithms, will derive new operational insights. Increased transparency and security will be made possible with blockchain as well.

As digital twins become more prevalent across the industry, there is great potential in orchestrating digital twin networks and enabling communications between two distinct digital twins.

Frequently asked questions

How do digital twins work?

Digital twins are virtual representations of physical products, processes, people, or locations that mirror and measure their physical counterparts in real-time. Data works in conversation, constantly uploaded and updated, providing digital twins with accurate information that users can trust to reflect what is happening in the physical world.

What is the history of digital twin technology?

Digital twin technology has been a concept since the 1960s, pioneered by NASA, who physically duplicated systems on Earth to match the systems in space. The NASA version of digital twin technology enabled the team to get the Apollo 13 crew home safely.

A new era of digital twins was ushered in by Michael Grieves, a faculty member at the University of Michigan, in 2002. He proposed a digital twin must have a connection between the physical and digital version. This definition persists today with IoT technology increasing the relevance, fidelity, and cost-effectiveness of digital twins.

Are digital twins considered AI?

Yes and no. Technically, a digital twin can be made simply by attaching a sensor to a physical object and recording its data. That said, many digital twins use machine learning (an application of AI) to process and analyze this information in a way that makes it actionable to the user.

What are digital twins in the metaverse?

Digital twins function in the metaverse (or spatial computing) much the same way they function in traditional computing. The industrial metaverse often makes use of spatial twins, which are location-based digital twins that provide real-world 3D context to workflow and operational efficiency.

Where are digital twins used?

Digital twins are becoming more common across multiple industries, including manufacturing, healthcare, construction, urban planning, oil and gas, aerospace and defense, automotive, and more.

They’re used in various roles and use cases across the product lifecycle from engineering to manufacturing to service.

What’s the difference between a digital thread and a digital twin?

A digital thread is the term used to describe universal access to data. It’s the connection synchronizing related upstream and downstream information from multiple sources and systems. A digital thread enables a more complete, real-time representation of a product, process, or person across enterprise functions.

This data unification of a digital thread is a prerequisite to building a robust digital twin.

How are digital twins different from simulations?

A simulation mirrors a physical process, place, person, or product—it never once measures its counterpart. It is an unanchored digital representation of a physical location but without the constant measuring and reflecting that goes on with a digital twin. Boiled down, digital twins can only exist if they have a physical counterpart while simulations do not necessarily need any real-world counterpart.

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