Digital twins in 2024: What it is, Why it matters & Top Use Cases

Simulations are indispensable but real world simulations are expensive. Therefore companies that need to learn fast (e.g. self-driving car manufacturers) heavily rely on simulations. Digital twins enable companies to simulate their shop floor or their entire business to identify optimization opportunities.

Today, businesses use digital twins in numerous ways from product development to operational performance improvement. The digital twin market is expected to grow to $73.5 billion by 2027, at a CAGR of 60.6%. ¹ Increased digitization and IoT adoption are making it easier for businesses to build accurate digital twins and drive adoption of the technology.

What is a digital twin?

A digital twin is a virtual/ digital replica of physical objects such as devices, people, processes, or systems that help businesses make model-driven decisions. The purpose of a digital twin is to run cost-effective simulations. These examples are costly to simulate without a digital twin, that’s why data scientists and IT professionals use real-time data to develop digital models that mimics the real-world assets in digital space.

The digital twin technology uses IoT sensors, log files and other relevant information to collect real world data for accurate modeling of assets. These models are then combined with AI-powered analytics tools in a virtual setting.

3 Types of digital twins

There are three main types of digital twins:

• Product Twins: Digital twin prototype of a physical object enables run-in scenarios to predict potential issues and optimize product quality.
• Process Twins: Process digital twins, also known as a digital twin of an organization (DTO), can help design, plan and improve processes to obtain best outcome.
• System Twins: Virtual replicas of systems obtain information generated by systems to manage and optimize them.

Why are digital twins important now?

According to the IoT implementation survey by Gartner, organizations implementing IoT already use digital twins (13%)  or plan to use it within a year (62%). ²

Digital twins can significantly improve enterprises’ data-driven decision-making processes. They are linked to their real-world equivalents at the edge and businesses use the digital twin technology to understand the state of the physical asset, respond to changes, improve operations, and add value to the systems.

How does a digital twin work?

These digital assets can be created even before an asset is built physically. Regardless of when it is created, the process of creating a virtual twin has basic steps:

1. Research the physical object or system that will be mimicked
2. Integrate sensors into physical assets or monitor log files and other sources to collect sensor data
3. All this collected information along is integrated into the virtual model with AI algorithms
4. By applying analytics into these models, data scientists and engineers get relevant insights regarding the physical asset.

These basic steps required to create digital twin simulations include major technologies which are the components of fourth industrial revolution (See Figure 1).

What are the benefits of digital twins?

Digital twins are commonly used in manufacturing and provide these benefits:

• Lower maintenance costs via predictive maintenance: Digital twins enable businesses to understand potential sources of failure so that businesses minimize non-value adding maintenance activities
• Improved productivity: Gartner predicts that industrial companies could see a 10 percent improvement in effectiveness via digital twins. This is due to reduced downtime due to predictive maintenance and improved performance via optimization.
• Faster production times: IDC claims that businesses who invest in digital twin technology will see a 30 percent improvement in cycle times of critical processes including production lines.

An emerging area for digital twins is creating digital twins of entire businesses by leveraging operational data, referred as a digital twin of an organization (DTO). Benefits in this area include:

• Improved business outcomes: Digital twins enable businesses to be more resilient to shocks thanks to virtual representations and this can translate into more enduring customer relationships and profitability.
• Improved customer satisfaction: A digital twin allows users to gain a deeper understanding about their services, potential disruptions and customers’ needs. As a result, businesses can deliver better, more consistent services that eventually enhance the customer experience.

What is the relation between AI and digital twins?

Artificial intelligence and digital twins have a mutualist relation where both contribute to each other.

Digital twins can help businesses generate simulated data that can be used to train AI models. Artificial intelligence can also benefit from digital twins since digital twins can virtually create an environment for machine learning test scenarios. Depending on the utility score of virtual environment data scientists and engineers can deploy artificial intelligence solutions.

Digital twins can benefit from artificial intelligence. AI and machine learning algorithms enable businesses both to build some digital twins and also to process a large amount of data collected from digital twins. For example, by leveraging AI capabilities with digital twins, engineers can accelerate the design processes by quickly evaluating many possible design alternatives.

What are digital twin use cases?

The capacity for aggregating actual data from a physical product, system or process opens the way for numerous new use cases. With the aggregation of real-time and historical data, digital twin technology enables businesses to simulate, diagnose, predict and design for different industries and applications.

Top industries with digital twin applications are manufacturing and supply chain. Feel free to read all digital twin applications in detail here.

In a review study, researchers collected academic publications that contain digital twin as a keyword for the years between 2017 to 2022.⁴ Among these academic articles, top digital twin use cases were found for urban spaces and smart cities.

What are the leading digital twin tools?

This is a list of digital twin providers, excluding digital twin of an organization vendors.

• Akselos
• Ansys Twin Builder
• Autodesk Digital Twin
• Bosch IoT Suite
• CONTACT Elements for IoT
• Flutura Decision Science
• IoTIFY
• Oracle IoT Production Monitoring Cloud
• Predix
• ScaleOut Digital Twin Builder
• Seebo
• ThingWorx Operator Advisor

If you want to create a digital twin for predictive maintenance purposes, we recommend you to read our comprehensive article about predictive maintenance.

Check out our sortable and data-driven list of digital twin software and digital twin of an organization (DTO) vendors to learn more.

If you still have questions about digital twins, don’t hesitate to ask. We would like to help:

External Links

• 1. “Digital Twin Market by Enterprise, Application, Industry and Geography – Global Forecast to 2027.” Reporterlinker. July 2022. Revisited on January 2, 2023.
• 2. “Gartner Survey Reveals Digital Twins Are Entering Mainstream Use.” Gartner. February 19, 2019. Revisited January 2, 2023.
• 3. Piromalis, D.; Kantaros, “A. Digital Twins in the Automotive Industry: The Road toward Physical-Digital Convergence“. Appl. Syst.Innov.2022,5,65. https:// doi.org/10.3390/asi5040065 
• 4. Botín-Sanabria, D.M.; Mihaita, A.-S.; Peimbert-García, R.E.; Ramírez-Moreno, M.A.; Ramírez-Mendoza, R.A.; Lozoya-Santos, J.d.J. “Digital Twin Technology Challenges and Applications: A Comprehensive Review.” Remote Sens. 2022, 14, 1335. https://doi.org/10.3390/rs14061335. Revisited on January 2, 2023.