5 Key Applications of Digital Twin Technology

Digital twin application
Video source: YouTube/MangKangMangMee
Table of Contents

Digital twins are changing the game in Industry 4.0, and businesses that use them stand to benefit in countless ways. They are particularly valuable in the industrial Internet of Things (IoT), engineering, and manufacturing sectors.

By bringing together state-of-the-art technologies like big data, artificial intelligence (AI), machine learning (ML), and IoT, digital twin technology can create virtual copies of physical objects and systems. 

This article will explore the exciting and innovative applications of digital twin technology and discover how businesses leverage its power to gain a competitive edge in their industries.

Digital Twin Technology and Its Basic Principles

A digital twin is a virtual copy of a physical object or system that uses data to simulate and predict behavior, performance, and maintenance.

The basic principles of digital twin technology are based on the idea of creating a digital depiction of a physical object or system that can be used to simulate and analyze its behavior.

This means that engineers and designers can create a virtual model of a product or machine and use it to test its performance, predict its maintenance needs, and even optimize its design.

The key to creating an accurate and useful digital twin is data. By collecting data from sensors, cameras, and other sources, engineers can create a virtual model that reflects the real-world behavior of the physical object or system.

This data can then be used to simulate different scenarios and analyze how the object or system will behave under different conditions.

Digital Twin Technology in Manufacturing 

Manufacturers are already experiencing the benefits of implementing digital twin technology, from speeding up product development to boosting productivity among front-line workers.

A study by Forrester Consulting, commissioned by Unity, revealed that over 80% of companies using this technology reported an improved ability to innovate and collaborate during the production, manufacturing, and operations phases. 

In manufacturing, they involve creating virtual replicas of physical equipment using real-time data from sensors and other sources.

Digital twins in manufacturing provide numerous benefits, including:

  • Reduced waste,
  • Improved throughput equipment longevity,
  • Preventive maintenance,
  • Asset ROI.

The more data inputs there are, the more accessible insights become. These insights can be used to improve machine maintenance practices and value stream monitoring, ultimately helping manufacturers to realize Lean philosophies.


Unilever, a manufacturing giant, has implemented an impressive use case of digital twin technology in its manufacturing processes.

The company began by creating eight digital twins of their factories in different regions of the world. By 2020, they completed over 100 digital manufacturing sites, providing a virtual model of their entire supply chain.

Through this approach, Unilever has increased productivity, minimized waste, optimized material usage, and ensured compliance and quality. Sensors installed in each factory monitor every process and send data to an enterprise cloud, where a digital twin is recreated.

On-site employees can easily access the digital twin data via handheld devices, enabling them to identify issues, develop solutions, and share data with colleagues.

This approach has helped Unilever streamline its manufacturing processes, increase efficiency, and maintain high-quality standards across all its sites.

Digital Twins in the Healthcare Industry

Digital twin technology is paving the way for more personalized and effective healthcare through the field of precision medicine.

It allows for the virtual model creation of a person’s body down to the molecular level, making it easier to tailor medical treatments to individuals based on their genetic makeup, anatomy, and behavior. 

Digital twin simulations allow medical personnel to predict outcomes before selecting treatment or therapy. 

As a result, problems can be anticipated before they arise, allowing ample time to implement necessary changes or follow appropriate procedures.

Digital twin technology can also be used in surgery to plan and practice procedures beforehand in a simulator, minimizing unintended structural damage.

Predictive analysis through simulation allows for detecting symptoms at an early stage and preventing and recognizing diseases at the right time.

With digital twin assistance, doctors have real-time access to information, allowing for better preparation and decision-making.

Video source: YouTube/BSC CNS


Philips has developed an innovative tool called the Dynamic HeartModel, which provides cardiologists with a clinical solution to evaluate acute heart functions for the precise diagnosis and treatment of patients suffering from cardiovascular disease.


The team of researchers at Siemens Healthineers has created an incredible computational model of a digital heart that can be accessed on a computer.

This innovative prototype can change precision medicine by giving doctors real-time predictive guidance during surgeries. This means that more patients could benefit from tailored therapies than ever before.


FEops, a European firm, has launched a groundbreaking platform called Heartguide. This platform uses advanced technology to create virtual copies of the heart or its substructures from cardiac scans.

By leveraging this technology, FEops aims to enhance and expand tailored care for patients with structural heart disease.

Digital Twins in the Automotive Industry

Digital twins have become increasingly popular in the automotive industry for simulating and testing new design concepts, optimizing production processes, and predicting vehicle performance under different conditions.

The primary advantage of using digital twins for automotive OEMs is detecting and addressing potential issues before they arise, saving time and money.

The technology has proven useful across the entire automotive lifecycle, from design and manufacturing to marketing and maintenance.


Bridgestone, a leading producer of tires and rubber, utilizes digital twins as a powerful tool to enhance its products.

They can predict how different driving conditions and styles will affect their tires by creating digital replicas of their products.

This assists vehicle fleets in selecting the best tire options for their specific needs, leading to longer product lifespans and a reduced risk of tire breakages.

Moreover, Bridgestone uses virtual models to design and test its products in a simulated environment.

As a result, Bridgestone can speed up its production by almost 50% by conducting tests virtually. In addition, digital twin technology allows the company to easily share virtual replicas of their upcoming products with their partners, streamlining the approval process.

Video source: YouTube/Groupe Renault


Renault, the French automotive giant, uses a cutting-edge technique called the product digital twin approach to create virtual replicas of their vehicles before manufacturing.

The process starts with crafting a digital model of the vehicle’s exterior, paying attention to even the tiniest details of the interior. Once the design is complete, the engineering team creates a virtual replica of the vehicle’s technological components, such as the engine, electronics, mechanics, and navigation systems.

In this way, Renault can conduct extensive tests before producing the actual vehicle. This helps ensure maximum safety and compliance with existing standards.

In addition, any necessary modifications can be made to the vehicle’s modules before the final design is assembled.

Ultimately, this approach enables Renault to create top-quality cars that meet the highest standards of excellence.

Digital Twin Technology in the Aerospace Industry

Aerospace is a complex industry where designing and building aircraft and spacecraft is a massively expensive endeavor. This makes getting everything right the first time crucial to avoid costly delays.

Digital twins have become a valuable tool in aerospace as they enable teams to visualize and interact with computer-aided design (CAD) models and other datasets in real-time 3D, improving decision-making across the entire lifecycle of a product.

Digital twins have various use cases in aerospace, including product development and prototyping. The 3D visualization capabilities allow designers, engineers, and other stakeholders to collaborate and evaluate design and manufacturing alternatives for complex systems.

They also enable simulation and training in interactive 3D or augmented or virtual reality (AR and VR), creating engaging training experiences that facilitate better knowledge transfer and safer workplaces.

Moreover, digital twins can simplify and optimize inspection, maintenance, and repair activities by creating work instructions in mixed reality from as-built models from design and manufacturing.

Lastly, they are also helpful in sales and marketing, as virtual showrooms and 3D product configurators empower buyers to explore every variation of aircraft and make purchasing decisions more confidently.


The world’s leading aerospace company Boeing has adopted digital twins to facilitate aircraft modeling, engineering, and design.

To deal with the challenge of handling large volumes of data, Boeing has created digital replicas of every asset and system involved in production, enabling better organization, management, and information extraction.

One example of this is an aircraft inspection application using AR technology and a digital twin of one of its planes. By leveraging the digital twin, Boeing was able to generate more than 100,000 synthetic images, which improved the accuracy of the machine learning algorithms used in the AR application.

Boeing intends to share the outcome of this important project with all supply chain stakeholders. With the assistance of digital twins, the aerospace giant can now predict how product components will perform under various conditions and make informed decisions about repairs and replacements.

In addition to these applications, Boeing is leveraging digital twins in manufacturing to calculate cargo balances, ensuring optimal and secure use of cargo space on board its planes.

Digital Twin Technology in the Construction Industry

The construction industry can optimize project data, streamline collaboration, and visualize projects better from design to operations and maintenance with the help of digital twin and AR technology.

AR technology helps contractors quickly capture and communicate design errors, allowing stakeholders to resolve issues and avoid costly rework.

Digital twins bridge the gap between a building’s design and function by cataloging critical information about its usage and assets.

They also link a building’s design and management, enabling space managers to monitor systems during construction and create credible sources for space governance and asset management when coupled with Integrated Workplace Management Systems (IWMS).

The digital twins’ top use cases in construction include the following:

  • Visualizing designs in real-time using AR,
  • Streamlining virtual design and construction workflows,
  • Providing immersive safety training,
  • Enhancing project close-out and maintenance by preserving essential model and project data to enhance the operation and maintenance of the digital twin long after the project’s completion.


Priva, a German-based company that integrates data-driven measures and digital twin technology into its systems, is an excellent example.

Its product ecoBuilding uses this technology and AI to predict the energy required to achieve optimal indoor climate while considering weather forecasts, building usage, energy generation and storage, and flexible energy prices.

Priva has implemented digital twin technology in buildings to save energy and costs while reducing CO2 emissions. The technology is still not widely used in buildings, but its rapid development offers enormous potential.

Its digital twin software has already achieved nearly 40% gas consumption savings and improved indoor climate. It can also be used to simulate energy networks and create intelligent buildings that adapt to users’ needs for optimal comfort and energy efficiency.

Wrapping Up On Digital Twin Technology Applications

Digital twin technology has shown its usefulness in various industries, such as:

  • Manufacturing
  • Healthcare
  • Automotive
  • Aerospace
  • Construction.

Businesses that use this technology can expect significant cost savings, increased productivity, and improved efficiency. In addition, using digital twins can enhance collaboration, innovation, and data insights.

Leading companies, such as Unilever, Philips, Bridgestone, Renault, and Boeing, have demonstrated how digital twins can be applied in real-world situations.

As digital twin technology continues to evolve and become more widespread, businesses should consider leveraging its power to stay ahead of the competition and achieve success.

Subscribe to our newsletter

Keep up-to-date with the latest developments in artificial intelligence and the metaverse with our weekly newsletter. Subscribe now to stay informed on the cutting-edge technologies and trends shaping the future of our digital world.

Neil Sahota
Neil Sahota (萨冠军) is an IBM Master Inventor, United Nations (UN) Artificial Intelligence (AI) Advisor, author of the best-seller Own the AI Revolution and sought-after speaker. With 20+ years of business experience, Neil works to inspire clients and business partners to foster innovation and develop next generation products/solutions powered by AI.