INTRODUCTION
A digital twin is a computer image of a physical entity or operation that acts as its real-time digital equivalent. Though the idea has been around for a while, NASA came up with the first realistic description of digital twin in 2010 as part of an effort to improve physical model simulation of spacecraft.The development of Digital Twins is the result of continual improvement of product design and engineering practises. From hand drafting to computer assisted drafting/computer aided design (CAD) to model-based systems engineering, product drawings and engineering requirements have advanced (MBSE).
TYPES
DIGITAL TWIN PROTOTYPE (DTP)
The DTP entails the development of physical products through designs, analyses, and processes. Before there is a physical product, there is a DTP.
DIGITAL TWIN INSTANCE (DTI)
Once a commodity is manufactured, the DTI is the digital twin of each human case.
DIGITAL TWIN AGGREGATE (DTA)
The DTA is a set of DTIs whose data and knowledge can be used to probe the physical product, predict outcomes, and learn more about it.
CHARACTERISTICS
Digital technologies have certain features that set them apart from other types of technology. These traits, in particular, have a number of ramifications. The below are the features of digital twins.
*Connectivity
The connectivity of digital twin technologies is one of its most distinguishing features. The Internet of Things (IoT) has recently advanced, bringing with it a slew of emerging technology. The Internet of Things (IoT) is hastening the growth of digital twin technologies. This technology exhibits a number of features that are close to the IoT’s character, including its connective nature. The technology, first and foremost, allows synchronisation between the physical dimension and its digital equivalent. This correlation is the foundation of digital twins; without it, digital twin technology does not exist. Sensors on the physical product establish this communication by collecting data and integrating and communicating it using different integration technologies. Increased collaboration between organisations, brands, and consumers is made possible by digital twin technology.
*Homogenization
Digital twins may also be described as a digital technology that is both a result and a facilitator of data homogenization.Since any kind of information or content can now be stored and distributed in the same digital medium, it can now be used to construct a composite version of the commodity (in the form of a digital twin), thereby decoupling the information from its physical form. As a result of the homogenization of data and the decoupling of information from the physical artefact, digital twins have emerged. Digital twins, on the other hand, allow an increasing amount of knowledge about physical objects to be processed digitally and decoupled from the object itself.
When data becomes more digitised, it can be distributed, processed, and computed in a more efficient and cost-effective manner. Moore’s law predicts that computational power will continue to grow at an exponential rate in the coming years, while computing costs will fall dramatically. As a result, producing digital twins would have smaller marginal costs, and measuring, predicting, and solving problems on abstract representations would be much easier than testing on actual models and waiting for physical products to fail before interfering.
The user experience converges as a result of the homogenization and decoupling of content. A single item may provide several new affordances as material from tangible artefacts is digitised. Digital twin technology makes it possible to exchange accurate details about a physical object with a greater range of agents, regardless of their physical location or period.
*Reprogrammable and smart
A digital twin, as previously mentioned, allows a physical product to be reprogrammable in a specific manner. Additionally, the digital twin can be reprogrammed automatically. The proliferation of functionalities is a result of this reprogrammable design, which is enabled by sensors on physical products, artificial intelligence technology, and predictive analytics.Again, using an engine as an example, digital twins can be used to gather data about the engine’s output and, if necessary, change the engine, resulting in a newer version of the component. Servitization can also be seen as a result of the reprogrammable nature.Manufacturers may be in charge of monitoring the digital twin, making changes, or reprogramming it if desired, and this can be offered as an add-on feature.
*Digital traces
The fact that digital twin systems leave digital traces is another feature that can be noticed.Engineers may use these traces and go through to search the traces of the digital twin when a computer malfunctions, for example, to diagnose when the issue arose. These diagnoses can be used by the machine’s designer in the future to change the architecture of the machine so that similar malfunctions arise less often.
*Modularity
Modularity can be described as the design and customization of products and production modules in the manufacturing industry. Manufacturers achieve the freedom to tweak models and equipment by incorporating modularity into their production models.Manufacturers may use digital twin technologies to monitor the equipment they use and identify potential areas for change. Manufacturers can see which components are causing the system to work poorly and replacing them with better fitted components to increase the production process as these devices are made modular using digital twin technology..
Applications of Digital Twins
Organizations can obtain better insights into product efficiency, optimise customer experience, and make more organisational and strategic decisions based on these observations by introducing Digital Twins. The following industries have begun to see significant uses of Digital Twins.
*Manufacturing:
The Digital Twin is set to transform the automotive industry as we know it. The way goods are developed, produced, and stored is significantly influenced by digital twins. It improves manufacturing efficiency and productivity thereby lowering throughput times.
*Automobile:
In the automotive industry, digital twins can be used to build a simulated image of a linked car. It records the vehicle’s behavioural and operating data and aids in the analysis of the vehicle’s overall performance as well as its related functionality. It also aids in providing consumers with genuinely personalized/customized service.
*Retail:
In the retail industry, providing a pleasant consumer service is crucial. By building visual twins for consumers and designing fashions for them on it, digital twin implementation will play a key role in enhancing the retail consumer experience. Digital twins also aid in more efficient in-store organising, security delivery, and energy management.
*Healthcare:
From cost savings to patient monitoring, preventative treatment, and delivering customised health care, Digital Twins and data from IoT will play a vital role in the health care industry.
*Smart Cities:
Smart city planning and deployment using Digital Twins and IoT data continues to improve economic growth, capital efficiency, environmental footprint reduction, and overall resident quality of life. Through gathering inputs from numerous sensor networks and intelligent technologies, the digital twin concept will assist city planners and politicians in smart city planning. The data from the digital twins also aids them in making better decisions about the future.
*Industrial IoT:
Industrial companies that have implemented digital twins will now digitally manage, map, and automate their processes. Aside from operational data, digital twins capture environmental data including location, configuration, financial models, and so on, which aids in the prediction of future operations and anomalies.
*Aerospace
Physical twins were used in aerospace engineering before digital twins. For example, during the Apollo 13 programme in the 1970s, NASA scientists on the ground were able to replicate the ship’s situation and discover solutions as crucial problems emerged. NASA’s John Vickers introduces the optical twin idea later in 2002.
Experts today recognise the role of digital twins in the aerospace industry, with 75 percent of air force executives voting in favour of the digital twin, according to a Business Wire survey study.
Engineers will use predictive analytics for digital twins to forecast any potential problems with the airframes, engines, or other parts, ensuring the safety of those aboard.
*Predicting the performance of packaging materials
Until being packaged, food packaging can be virtualized and checked for defects. Logistics firms will use digital twins to assess content viability.
*Enhancing shipment protection
With the assistance of digital twins, logistics firms will see how different packaging environments impact product distribution.
*Optimizing warehouse design and operational performance
Logistics firms may use digital twins to evaluate warehouse configurations and choose the most effective warehouse configuration to improve operating efficiency.
*Creating a logistics network
The details included in a digital twin of a road network includes traffic conditions, road configuration, and building. Logistics firms can plan delivery routes and product storage locations using this information.
CONCLUSION
Digital Twin applications have been used in a wide range of markets, changing the way companies work. Digital Twin technology uses IoT sensors, XR capabilities, and AI-powered analytics to predict asset maintenance requirements, reduce operating costs and asset downtime, and improve overall business performance.Furthermore, the Digital Twin enables the testing of “what-if” scenarios against market goals, allowing for the most precise decisions possible. Digital twins have a real-time view of what’s going on in physical infrastructure, which can significantly reduce repair costs.