Digital Twin Technology is the digital replication of any physical asset or processes used for problem-solving and decision making. The three main components of the digital twin -physical assets, virtual simulation, and connected data- are combined to establish interaction between the virtual and real worlds.
The digital twin is gaining popularity faster due to a list of unique benefits that this emerging technology provides. For example, it can work from any place, generate real-time data, analyze and provide a clear report of the state of a machine, aiding decision-makers.
For example, the largest agricultural machinery manufacturer, Stara, has replaced its traditional production processes with Digital Twins to increase production efficiency and customer experience.
Google Maps have changed rapidly using the Digital Twin of the natural world using a massive amount of time-based data from a specific location of the world. The Digital Twinning of Google Maps shows us the geographic location and provides helpful directions to find the way to our destination.
Digital Twin is one of the emerging technologies of the future. Furthermore, AI, IoT, and massive data have shaped the Digital Twin into powerful technology. Yet, most industries haven’t adopted Digital Twin. However, the scenario is changing faster after the Covid-19 pandemic shock.
The Impact of Digital Twins in industries:
Catapult, a wearable technology company, has surveyed engineers to deduce the value that companies can derive by using Digital Twin technology at different stages of the lifecycle.
We must review these stats to see the big picture and understand the impact of Digital Twins in various industries. According to the Catapult survey:
- 77% of engineers believe that digital twin adds the most outstanding value for maintenance, repair, and operations of products
- 70% of engineers believe that the manufacturing stage of the product lifecycle will benefit highly from Digital Twin applications.
- 62% of engineers believe that Digital Twin use can be effective during the simulation of a model to predict the present and future behavior of the final product
- 60% of engineers view Digital Twin as an efficient tool to use for quality control testing.
- 59% of engineers believe that the digital twin is impactful in the design phase of product development.
- 32% of engineers think that predicting future events can push the technology to achieve the desired objectives.
Benefits of Digital Twins Technology in Business:
The benefits of digital twins are different for different industrial uses. However, the most common benefits of Digital Twins include:
- Build prototypes of products before manufacturing
- Predicting failures before they occur, detecting defects, and reducing maintenance costs
- Making sure that production goals are not affected by repair or by frequent replacements of parts
- Enhancing product quality through performance testing in real-time
- Improving products through continuous analysis and customization
- Shortening the product development cycle and ensuring faster launch
Read more: The Future Digital Twin: What Role Will Digital Twin Play in the Next Ten Years?
Digital Twin Applications Use Cases in a Few Industries:
Digital Twin applications are suitable for a wide variety of industries. Here we’ve just documented a few digital twin use cases below.
Digital Twins in the Automotive Industry:
Digital twins technology in the automotive industry has brought a massive revolution. Automobile companies are developing cars primarily in the virtual environment. Undoubtedly, it’s fascinating.
Automobile companies plan the entire manufacturing process in the virtual environment using the Digital twin of production. This type of digital twin helps to determine how all compartments of the car will come together.
A digital twin of production also helps test and optimize new production lines to reduce time, workload, and risk for developing the physical car.
On the other hand, the digital twin of performance has significantly improved quality management and data analytics for automobile production.
The Digital Twin of performance generates new insights about the production line by following a step-by-step process. First, the shop floor will feed essential data in the cloud system. The cloud system will then analyze the data to help optimize every stage of the production.
Digital Twin in Healthcare:
The digital transformation of the healthcare industry is breathtaking as well. For example, the use of the Digital Twin technology in healthcare has helped to develop digital twins of organs and other anatomical structures, personalizing the medical devices to meet the individual needs of patients.
For instance, Dassault Systèmes SE, a French software company, developed a Digital Twin heart using MRI images and ECG measurements. This digital twin heart replicates the structure and some functions of the human heart. Now, heart surgeons can feed the patient data into the Digital Twin heart to determine whether the surgery will be successful.
Dassault Systèmes SE has launched the Living Heart Project in collaboration with academic and industrial members like Medtronic, Philips, and Boston. All the Living Heart Project members are working together to build safer and effective cardiac devices for patients.
The Digital Twin is no longer a hypothesis in the healthcare sector as it’s already in use and expanding to make procedures of organ donation and surgery safer.
Digital Twin in Airline Industry:
Digital Twin in the airline industry is helping both the airline companies and jet engine producers to make critical decisions faster. In other words, digital twins are making it easier for them to analyze an extensive fleet of engines at a time. As a result, they can monitor risks and optimize operations to ensure safety, and develop new services that can be valuable to the customers.
The jet engine is typically dismantled every 20 to 24 months to examine the parts and repair if necessary. Today, the Digital twin technology in the airline industry collects and analyzes about 2,000 critical characteristics of the jet engine to measure its performance. The digital twin also predicts the timing of the aircraft maintenance inspection.
In this way, the airlines can avoid significant disruptions in their daily flight schedules. They can provide the services as promised to their customers.
How do companies use Digital Twins?
Companies use Digital Twins in different ways at different times. So, we can say that there are three types of Digital Twins based on the timing of the use:
Digital Twin Prototype (DTP)
Manufacturers start working on the product at The DTP. At this stage, manufacturers design, analyze, and plan out the process to predict the future shape of the actual product.
Digital Twin Instance (DTI)
The companies manufacture the physical product and build DTI. In other words, DTI is the twin of a physical asset. Developers will use DTI to run multiple tests and determine how the product will behave in different scenarios.
The DTI stays connected with the physical asset throughout its lifecycle. As a result, developers will add more operational data to improve it over time.
Digital Twin Aggregate (DTA)
The DTA is the aggregation of DTIs. Companies use DTA to cross-examine the physical product, predictions, and learning based on the collected data from the previous phase.
As you can see, companies use three types of Digital Twins for product development and re-designing, quality control and management, etc.
Read more: Why Accenture Lists ‘Digital Twins’ in Top-Five Technology Trends in 2021
How does a digital twin work?
The Digital Twin technology must have the ability to simulate and capture the undergoing events of the actual product to gather valuable insights on performance and future problems. So, the developers make sure that the Digital Twin is constantly receiving feedback data through sensors from the authentic product.
Components of Digital Twin are connected to a cloud-based system to analyze all the data received from the sensors against the existing business or contextual data. The data analysis in the cloud-based system helps to unfold new opportunities within the virtual model. Finally, developers apply these opportunities and scope to the actual product.
Digital Twin can also help determine the tests the manufacturers should run more often to improve the product.
Digital Twin is often developed alongside the actual product as a prototype to get feedback at any particular stage of its development. Sometimes the Digital Twin will be built as a prototype before the actual product comes into existence to determine future performances or failures.
Digital Twin can be simple or complex as you wish it to be. How accurately the Digital Twin will replicate the physical object will depend on the amount of data you are feeding into the Digital Twin.
Conclusion:
As we have mentioned above, that Digital Twin technology is not a hypothesis in the industries anymore. It’s the new reality that’s already in use, and manufacturers are benefiting from it.
According to Gartner reports, 13% of IoT-based companies are using digital twins already. In addition, 62% of the companies aware of Digital Twin are either establishing Digital Twin or planning to in the future. The Gartner report also claimed that 50% of the large industries would use Digital Twin Technology in 2021. Thus, they will achieve a 10% improvement in production efficiency.
With the rise of the popularity of emerging technology, companies are deploying AI, machine learning, software analytics, and cloud connectivity to empower the Digital Twin.
