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Mikhael Khaimov


Exploring the Business Value of Digital Twins

How digital twins are shaping the future

Published: Wednesday, February 16, 2022 - 13:02

Today thousands of technologies and solutions help businesses improve efficiency, create better products, evolve faster, and so on. A digital twin is a technology that deserves a closer look, especially if your goal is to improve business performance and reduce costs.

What’s a digital twin, and how does it work?

In the simplest terms, a digital twin (DT) is an exact, detailed, and dynamically updated digital replica of something in the physical world (e.g., objects or processes). A digital twin is run in a simulation environment to:
• Monitor performance and efficacy
• Test different scenarios
• Predict issues
• Find optimization opportunities

Unlike traditional computer-aided design and engineering (CAD/CAE) models, a DT receives live data from its real-world counterpart and changes accordingly through its life cycle.

The term “digital twin” was first used in 2002 by Michael Grieves at the University of Michigan. However, the concept of a digital twin has been around since the 1960s at NASA, when it was called a “living model,” and was later used during the Apollo 13 mission.

However, thanks to internet of things (IoT) technology, DT became affordable and accessible to more businesses. That’s because IoT sensors can gather data from the physical world and send them to machines to reconstruct as digital versions. Doing so allows us to learn about particular systems, predict different issues, increase efficiency, and so forth.

DT can revolutionize healthcare, manufacturing, real estate, and other industries. For example, it’s used at NASA to explore next-generation vehicles and aircraft, and elsewhere to refine Formula 1 car racing and create virtual copies of TV hosts, among other applications.

Thus, the digital twin market is expected to reach $48.2 billion by 2026, a compound annual growth rate (CAGR) of 58 percent from $3.1 billion in 2020. What’s more, according to the forecast, 13 percent of organizations with IoT projects implemented already use digital twins, and 62 percent are either in the process of establishing DT use or are going to do it.

Digital twin types

There are four types of digital twins, which are explained below. Combining and integrating all of them is known as the digital “thread” because it’s woven into, and brings together, data from all stages of the product and production life cycles. So, let’s consider the digital twin types you can use depending on your demands.

Chart  Description automatically generated
Credit: The Constructor

Component twins

Part twins or component twins are the basic levels of twinning. The virtual representations of the individual components allow engineers to understand and evaluate the durability, resilience, physical, mechanical, energy efficiency, and other crucial characteristics of a part. In this way, they can analyze how the part will behave in real-life scenarios.

Asset twins

This is the next level of twinning—creating the digital replica of the entire product. Asset twins enable you to explore an entire system and study the interaction of the components. Asset twinning generates a wealth of performance data you can process and then turn into actionable insights. It allows for:
• Optimizing the constituent parts
• Maximizing operating characteristics
• Minimizing things such as a mean time between failures (MTBF) and mean time to repair (MTTR)

This shortens development time and allows for faster iterations.

System twins

System or unit twins go further and enable engineers to see how different assets come together to form an entire functioning system. They not only provide visibility regarding the interaction of assets but also suggest performance enhancements. System twins can be used for all the different types of applications.

Process twins

In this case, complete virtual models of the production steps are created. Process twins provide insight into the collaboration of all units, reveal how systems work together to create an entire production facility, and help determine the precise timing schemes that ultimately influence overall effectiveness and prevent costly downtimes.

Process twinning will enable companies to monitor key business metrics in a much more data-driven manner. This approach helps to clarify:
• How much time is needed to produce a particular product
• How much it will cost
• What can be automated

Business benefits of digital twins

The main point of the digital twin is to digitize existing processes so businesses can operate with maximum efficiency in real time. Let’s take a brief look at how leveraging this advanced technology can provide business value.

Data-driven decision making. Digital twins create a comprehensive virtual representation of all company processes to provide a business-level perspective for measuring and analyzing the entire organization’s performance. Businesses can model alternative approaches and restructure entire processes based on hard data, rather than making decisions based on generalized assumptions.

Reduced costs. Usually, a product goes through several iterations before a functional prototype is created. This process is time-consuming and expensive. DT allows engineers to perform tests and simulations in a virtual environment to reduce defects during actual production. It’s much easier, cheaper, and faster.

More effective research and design. Improvement in research and development (R&D) processes is assured, thanks to the valuable insights DTs offer about customers, processes, mechanisms, and connections received.

Innovation-based product changes. Digital twins help improve the design of physical products throughout their entire life cycle by pre-analyzing the actual product during its development phase. By combining operational network information with data from connected assets, enterprises can create a digital view to manage and maintain infrastructure to deliver better services.

Improved business operations. Digital twins can improve interactions and workflows between different departments, such as product development, sales, maintenance, and engineering. In this way, enterprises can ensure continuous improvement and sustained profitability by identifying performance gaps.

Product life cycle management. Product development used to be a costly process, because it involved generating multiple prototypes and conducting various tests. Digital twins allow engineers and manufacturers to test their designs in any environment, at any stage, until the perfect solution is found. What’s more, digital twins can re-create any medium, even unrealistic ones, which enables engineers to ensure their designs are bug- and defect-free.

Reduced time to market. Digital twins used to create a product or service can reduce the time to market. A virtual prototype allows you to test how a physical product would perform in reality, thereby optimizing efficiency and development time. Because the product life cycle takes place in a digital environment, all improvements can be made faster and easier.

Increased customer value and satisfaction. A DT can identify and collect user feedback to pinpoint design flaws and other issues. This insight then goes to your engineering and technical departments, where they can improve the product according to customer expectations. Product customization is also possible.

Industries that use DT technology

The concept of digital twins has gained traction in many fields, including supply chain management, predictive maintenance, and remote equipment diagnostics. Today, digital twins are being used by a greater segment of industry—and considering the benefits for businesses, it’s no surprise at all. Below are some real-life examples of how DT works in different industries. 

Automotive and aerospace

As cars and aircraft comprise many complex, co-functioning systems, digital twins are widely used to improve vehicle performance and make their production more efficient.

Automakers such as Porsche and BMW are already developing cars of the future by using digital twins. Companies can now create all sorts of prototypes at no extra cost.

CAD tools that were static and didn’t offer dynamic reviews are now transformed with real-time renderings. Crash tests can be simulated, and physics parameters can be adjusted to see how a car will behave on different road conditions or in unique situations.

DT not only allows crash tests but also gaming technology to train driver assistance systems with synthetic sensor data. Playing out each scenario in detail helps verify safety requirements and creates vehicles that can respond properly without involving the driver.

Boeing uses digital twins in aircraft design to predict the performance of different components throughout a product’s life cycle. As a result, the company’s engineers can anticipate when products might fail.


In retail, digital twins can come in handy both in the supply chain and the store. With digital twins, retailers now have the ability to:

Manage the supply of merchandise efficiently. Digital twins help retailers identify bottlenecks, supply shortages, and demand curves within seconds. Based on these data, they can restock merchandise, adjust product placement, and create targeted ads to minimize losses and drive sales.

Avoid supply chain disruptions. Retailers can combine their DT models with real-time external data, such as local traffic and weather. Thus, they can respond proactively to any events that might disrupt the supply chain.

Optimize logistics cost. French supermarket chain Intermarché created a digital twin of the brick-and-mortar store based on data from shelves and shopping systems equipped with IoT. Store managers can now easily manage inventory and test the effectiveness of different store layout options.

Urban planning

Civil engineers and others involved in urban planning are aided by DT, which can show 3D and 4D spatial data in real time, as well as introduce augmented reality systems into a built environment.

The brightest examples of DT use in urban planning are:

Smart cities. Using video cameras, edge computing, and artificial intelligence, information can be obtained for everything from parking and traffic flow to crime dynamics. Urban planners can study these data to help develop and improve city design. Singapore has a digital twin that for some time has been helping people with limited mobility; the city council uses modeling to remove architectural barriers.

Water supply. Water utilities use digital twins to ensure an uninterrupted water supply and better prepare for emergencies. With DT, they can get an accurate assessment of the current water system’s performance, identify problems before they occur, and simulate what-if scenarios. Aguas do Porto (AdP), the Portuguese utility responsible for the water supply of the city of Porto, uses DT to predict floods and other issues, improve the quality and responsiveness of city services, and ensure water facilities’ sustainability.

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Grid digital twin comprising the asset twin and network twin. Credit: Energy Market Authority


Digital manufacturing twins enable manufacturers to simulate and optimize their production systems, including logistical aspects, and provide a detailed visualization of the production process, from individual components to the entire assembly.

Sensors collect various operational data from the equipment so that the digital twins can combine and analyze the data. Then, if deviations in performance are detected, engineers can optimize production processes in advance.

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Credit: Behrang Ashtari, Michael Weyrich

Kaeser, a leading supplier of compressed air equipment, has used DT technology to go from selling a product to selling a service. Its DT system continuously provides up-to-the-minute data, particularly about air consumption, on equipment during its life cycles. This monitoring allowed Kaeser to charge customers based on air consumption rather than on a fixed rate. As a result, revenue grew.

Real estate

In real estate, a digital twin can contain a whole spectrum of data concerning the building itself:
• Floor plans
• Real-time sensor data from the building management system
• Data from the heating, ventilation, and air-conditioning (HVAC) system
• Security system
• Environmental sensors monitoring lighting and fire
• Data about assets and people (e.g. tenants, staff, and visitors)

digital twin in real estate
Credit: Azure

In this industry, the main purpose of a digital twin is to understand a building, predict and prevent potential performance and maintenance issues, and find new ways to get more revenue from the building.

These are the core functions that real-time DT analytics provide to real estate owners and operators:
• 24/7 overview of floor plans
• Real-time performance data of any equipment piece
• Digitized documentation
• Maintenance schedule
• Issues history

digital twin in real estate
Credit: InVision

So, the digital twin is the ultimate real-time database of a building’s ecosystem. Within hours, building operators can identify an area that needs modification and find the most cost-effective ways to do so.


The utility industry constantly looks for ways to improve operational processes, reduce unplanned outages, and monitor market conditions. Digital twins can model and monitor a unit’s condition, thereby changing the way utilities operate.

Remote assistance. With DT, assets such as solar panels, wind turbines, boilers, compressors, and pumps can be supervised remotely. If problems occur, required support can be provided remotely, too.

Asset visualization. If a company wants to introduce a complex utility product at a trade show, there’s no need to transport it to a faraway location. Instead, they can use an exact digital replica for installation.

Asset performance management. Using continuous industry data about energy and renewable resources, executives can monitor company operations accurately, easily evaluating resource health, process efficiency, and equipment reliability. What’s more, predictive diagnostics enable digital twins to predict potential equipment troubles and failures to reduce unplanned downtime.


The outbreak of Covid-19 caused DT technology to gather momentum in healthcare diagnosis. It can be used to inform and manage decisions about general medical services, and to assist research and development.

By creating digital twins of hospitals, operational strategies, patient care patterns, and staffing, medical companies can determine what actions to take to provide personalized, data-driven medical care. They can also optimize patient care, reduce costs, and improve efficiency.

Researchers and healthcare professionals can’t apply new drugs, procedures, or practices to someone before they’re properly tested due to the risks involved. However, digital twins can supply real-world data to help test new products or services and speed the process.

In healthcare, DTs are used to provide:
• Virtual organs for clinical diagnoses, education, and training
• Personalization of patient information to administer the right treatment faster and allow doctors to monitor patients remotely
• Scanning of the whole body for more-accurate diagnoses
• Surgery planning and optimization 

Implementing the technology

Digital twin simulations have been around for half a century. However, only now has this technology been widely adopted by companies to optimize design, production, maintenance, marketing, and merchandising.

Digital twins can connect countless solutions, machines, and processes in one working system. By using advanced technologies, such as machine learning, artificial intelligence, and augmented/virtual reality, DTs generate valuable insights to expand a business and help it gain a competitive advantage.

Thanks to DTs, it’s now possible to:
• Design complex what-if simulations
• Backtrack from detected real-world conditions
• Perform simulation processes without overwhelming systems

As part of the process of adopting DTs, businesses should consider the following:

Security issues. The amount of data collected by the technology from numerous endpoints is really huge. What’s more, each endpoint represents a potential area of security vulnerability. Companies should be ready for that; before adopting digital twin technology, they should update security protocols and do an assessment.

Data quality. The technology depends on data from thousands of remote sensors. To work correctly, all the data must be relevant and of high quality. A company must be able to exclude bad data and manage gaps in data streams.

Learning curve. A company should be aware that this technology isn’t simple and requires certain skills and tools. It’s important to train a team first and provide all the needed solutions to work with a DT.

High cost. Adopting the technology requires certain investments at the beginning. It’s a good idea to plan a budget prior to implementing DT so that it brings the expected benefits.

Digital twins will only get more popular. Study results indicate:
• By 2025, 89 percent of all IoT platforms will include digital twins
• By 2027, digital twins will be a standard IoT feature

Digital twins are shaping our future. The technology not only helps perfect various processes and operations but also unlocks new approaches and solutions for better living, working, and being. DT technology is forecast to evolve during the next several years. So, if you produce a complex product and want to gain an advantage over competitors, it’s worth implementing.


About The Author

Mikhael Khaimov’s picture

Mikhael Khaimov

Mikhael Khaimov is a CTO at DDI Development. He is a professional with an advanced degree in web development and 13 years of experience in building a technology strategy for the company’s projects. He has a deep understanding of network security, compliance, and operational security.