Ever imagined you could view inside a machine, streamline its performance, and forecast its future? Yes, digital twin technology makes it possible!
Do you know what a digital twin is? A digital twin is the digital counterpart of a physical asset. The digital replica is continuously updated with data gathered from the sensors attached to the physical object. The data collected helps reflect the real-time performance of its physical twin.
It covers the object’s lifecycle and makes use of simulation and machine learning. The updated data helps you to gain useful insights and further help you make decisions.
So, how does a digital twin work? In this article, we will discuss it in depth, along with the types of digital twins, their advantages, and more.
How Does a Digital Twin Work?
Think of physical assets such as wind turbines, which possess several sensor networks. The sensors monitor the machine’s performance and collect data on temperature, environmental conditions, and energy generation. The collected data is later sent to a processing system, which updates the digital representation of wind turbines.
When provided with useful data, the digital replica can be used to carry out several simulations, analyze performance issues, and develop possible advancements. The fundamental purpose is to gain valuable insights to improve the real physical object.
Digital Twins Versus Simulations
Both simulations and digital twins leverage digital models to show the several processes involved in a system, but digital twins provide a better scope for analysis.
A simulation, in general, focuses on a single process, while a digital replica can run several useful simulations with the help of sensor data collected in real-time from the physical object/process/system it represents.
Also, the two-way information flow is one of the reasons for the major difference. As we know, there are sensors in the physical system/object, and they send data to the digital twin nonstop.
Later, they use the data to implement performance analysis and predict potential problems. The insights gained from the data analysis are later sent to the physical system for proactive maintenance and optimization.
The integration of real-time data with the virtual environment strengthens digital twins’ ability to discover several scenarios. Further, it helps them access in-depth insights as opposed to conventional simulations. Top of all, it has the capability to improve product design, process efficiency, and performance.
What are the Different Types of Digital Twins?
Generally, several types of digital twins exist within a process or system. To understand this clearly, we shall dive deep into the types of digital twins. Let’s learn the differences between them and see their applications.
Component Twins or Parts Twins
The basic part of a digital twin is the component twin. In fact, it pays heed to the functionality of individual parts. The same applies to the parts twin and is used for components with a bit less crucial role.
Asset Twins
Typically, when several multiple components function together, they may be referred to as assets. Asset twins facilitate communication between the physical asset’s components. In the end, they are considered useful for generating valuable data. The collected data gets transformed into actionable insights for optimizing and streamlining an organization’s performance.
System Twins or Unit Twins
Unit Twins helps you understand how the different assets unite together to form a complete functioning system. It also offers insights into the asset interaction and reveals opportunities for performance improvements.
Process Twins
Process Twins verify whether all the systems are synchronized to perform at their peak efficiency and whether the delays in one system affect the others. They also help analyze precise timing schemes and optimize the production process.
History of Digital Twin
The concept of creating a digital replica for a physical object/process/ system dates back to 1991 when David Gelernter’s book ‘Mirror Worlds’ talked about this novel idea. This laid the rich foundation for future developments in digital twins.
The term ‘digital twin’ was first used by Michael Grieves in 2002, and it focuses on its use cases in the manufacturing sector. This has formally announced the arrival of digital twin technology.
Having said that, the concept of using a digital twin to study a physical object has been implemented much earlier. For example, during the 1960s, the National Aeronautics and Space Administration (NASA) first introduced the use of digital twin technology for its space exploration.
Each voyaging spacecraft got its Earth-bound replica that duplicated the original spacecraft’s design and operation. Further, it simulated several scenarios and served as a training ground for NASA personnel on flight crews.
What are the Advantages of Digital Twin?
The following are some of the key advantages of digital twin technology. Let’s go through them in detail.
Enhanced R&D
Thanks to the data generated on the possible performance results, the information so collected helps to derive valuable insights to help companies with the most necessary modifications before they begin the production process.
Higher Efficiency
Creating a digital replica helps even during and after the production process, where it mirrors and tracks production systems. The basic purpose is to achieve and maintain top efficiency during the manufacturing process.
Decisions on Recycling Products
Digital twin technology helps businesses make decisions about products that reach the end of their lives, such as recycling or other similar steps. With the help of digital twins, they get a clear idea of the product components that can be reused.
Digital Twin Market and Industries
While it offers a robust suite of capabilities, Digital twins are not a one-size-fits-all solution. For example, not every object is very complex enough to justify the intense flow of sensor data required by digital twins.
Also, the cost may not be viable for every situation because a digital twin is not an exact replica of a physical system or object. On the other hand, there are several project types that can benefit from using digital twin models. Let’s see each one of them.
Industries Benefiting from Digital Twin Technology
Physically big projects such as huge and complex structures that follow stringent rules of engineering, for example, bridges and buildings.
Mechanically complex structures such as aircraft, automobiles, and jet turbines where the digital model helps enhance efficiency with respect to the machinery and engines involved.
Power machinery covers mechanisms for generating power and its transmission.
Manufacturing industries where the digital model can optimize processes efficiently.
To make it even more clear, digital twin technology is helpful in industrial sectors involving large-scale production, for example:
- Building Construction
- Manufacturing
- Engineering System
- Automobile and Aircrafts
- Railcar Design
- Power and Energy Utilities
Digital Twin Market: Sprinting Toward Growth
The ever-expanding digital twin market shows its usability across a wide range of industries. The demand for digital twins will grow in the future. According to mckinsey.com, the market estimates for digital twin investments is expected to reach above $48 billion by 2026.
What are the Applications of Digital Twin?
Typically, digital twin technology is used in the following areas.
Engineering Structures and Systems
Large physical structures, such as massive buildings, benefit from creating digital replicas by helping with their design. This is also helpful for designing systems functioning in these large structures, such as heating, ventilation, air conditioning (HVAC) systems, and electrical grids.
Manufacturing Processes
Digital Twins are meant to replicate a product’s entire lifecycle. They become useful at all stages of manufacturing operations, such as manoeuvring products from their design to the final stage and all those phases in between.
Healthcare and Wellness Services
Just like you can assess a physical product with the help of its digital replica, healthcare services also benefit from the technology. The data collected from sensors helps monitor health indicators and enables healthcare professionals to gain valuable insights.
Automotive and Automobiles
Digital Twins are widely used in the automotive industry for design purposes, enhancing vehicle performance and boosting efficiency during the production process.
Urban Planning
With the help of digital twins, engineers involved in town planning activities can rely on digital replicas where they can make use of the 3D and 4D spatial data in real-time. Additionally, it integrates AR systems in the built environment.
Frequently Asked Questions
What is a digital twin, in simple words?
A digital twin replicates a physical object’s features and behavior. Smart sensors that collect data from the product create a real-time digital representation of the asset.
Does digital twin technology use AI?
With the application of AI, digital twins transform themselves into proactive tools. They learn from real-world assets instead of merely replicating them. Businesses can anticipate potential issues, streamline process flow, and improve decision-making.
How are digital twins useful?
Digital twins use real-time data and provide insights that can change the way their real-world, physical versions operate. Industries such as manufacturing, maritime, urban planning, aviation, farming, and agriculture are already using this technology to make their processes more reliable, safe, and efficient.
Read more: How Can Telecom Industries Enhance Transformation With Digital Twin Technology
The Future is Here: Digital Twin Is Revolutionizing Industrial Sectors
Every day, we witness radical changes in existing operating models in asset-intensive industries. As a result, operating models also change accordingly. To incorporate the changes, it requires a more specific integrated view of assets and processes. For example, it expands to the physical as well as digital realm.
The future of digital twins is endless as they continuously learn new skills and abilities. This further translates into enhanced capabilities and its prowess in generating useful insights. It further helps design and produce better products and ensure process efficiency.
At ThinkPalm, our flagship industrial IoT platform, NetvirE, acts as your digital twin by creating the replicas of your assets. Further, it can turn your data into actionable insights. These valuable insights strengthen your business and improve industrial workflow effortlessly, reduce cost and energy consumption, perform predictive maintenance, customize products, monitor products from beginning to end, and many more.
Contact our IoT app development team and explore the best way to streamline your industrial process flow.
Author Bio
Silpa Sasidharan is a content writer and social media copywriting expert working at ThinkPalm Technologies, who aspires to create marketing texts for topics spanning from technology, automation and digital business solutions.
