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Digital twin technology simplified: A guide for beginners

30‏/06‏/2023

Martin Petkov

Digital twins are virtual duplicates of a physical object or system that works with technologies like artificial intelligence, the Internet of Things, and data analytics to anticipate performance. The concept was created decades ago by NASA for their Apollo mission and has gained rapid growth in recent years in sectors like healthcare, retail, manufacturing, and energy. This blog explains what digital twins are, how they are created, and how they work. The types of digital twin models from component, asset, and system twins are discussed to understand their applications. The blog will also highlight how companies like General Electric, Shell, and Seimens lead in the digital twin space.

What is digital twin technology?

A digital twin is a virtual simulation of a physical object or digital system during its life span. It is continuously updated based on real-time data to simulate scenarios and track operations. Digital twins also use machine learning (ML) algorithms to predict performance and prevent issues before they occur, reducing downtime and maintenance costs. Data shows this technology is rapidly advancing, with expectations to become a standard tool in several industries. Grand View Research predicts the digital twin market will touch $86 billion by 2028.

Digital twin technology has applications across manufacturing, aerospace, and healthcare industries. For instance, an engineer can digitally replicate a jet engine to identify faults and improve maintenance. Alternatively, software developers can use digital twins of systems like a computer networking architecture to simulate cyberattacks virtually.

How is a digital twin created?

The creation of digital twins involves importing conceptual 3D models via building information modeling (BIM), computer-aided design (CAD), or geographic information systems (GIS) or scanning a physical, real-world model so users can visualize them virtually for analysis. Internet of Things (IoT) data is collected using sensors and actuators attached to the physical entity being analyzed to present them as interactive visualizations through the digital twin.

How does digital twin technology work?

Several technologies work together to allow digital twins to function seamlessly; they are listed below:

  • Internet of Things (IoT): This technology facilitates device-to-device and device-to-cloud communication and data flows enabled through computer chips and high-bandwidth telecommunication. Digital twins can collect data from IoT sensors placed on real-world assets to update the digital replica in real-time. This data can include information about the physical asset’s physical properties, like dimensions and material, and performance data, like temperature and pressure. This real-time data monitoring allows digital twins to flag issues, prevent problems, and improve regular maintenance.

  • Artificial intelligence (AI): Machine learning (ML), an AI technique, is used by digital twins to collate and analyze the data collected through IoT sensors. ML algorithms can process large amounts of data to identify patterns and predict the performance of real-world assets in different situations. These insights help optimize performance, maintenance, and efficiency.

  • Simulations: Engineers, technologists, or manufacturers can use the data from digital twins to test various ‘what if’ scenarios and predict future performance. The digital twin can evaluate the physical asset’s performance under stress, damage, and environmental factors. This analysis can be helpful for industrial equipment and infrastructure where conducting physical tests is expensive and cumbersome.

What type of model can be involved in a digital twin?

Companies and organizations create digital twins for various physical and virtual entities, including:

  • Component twins: These are considered the basic unit of a digital twin that represents a specific part of an asset or system, like gears and screws. Twins are created only for the most integral components of a product or system prone to stress and heat. Component twins can help designers simulate and model the best parts through improvements.

  • Product or asset twins: These are product simulations created with multiple component twins used to prototype an object to analyze and optimize performance before it goes into production. This model type helps visualize how multiple components work together, design the ideal product, and identify real-world product integrity. For instance, an engineer can create a digital twin for a wind turbine to assess its performance and predict failures due to damage over time.

  • System twins: These twins represent the working of various assets as a unit which can help improve efficiencies, productivity, and performance. Product manufacturers can create a system twin for an entire factory.

  • Process twins: Process twins replicate the collaborative functioning of components, assets, and systems. These virtual twins help evaluate overall effectiveness and efficiencies in processes to avoid errors and delays. For example, an organization can build a digital twin of their manufacturing processes to optimize operations, ensure safety, speed up production time, and reduce costs.

  • City twins: City developers can build a digital twin of a city or urban area to simulate situations and optimize planning by evaluating city development scenarios to ensure plan effectiveness, sustainability, and durability. These digital twins also allow planners to analyze and build optimal cityscapes considering traffic, emergency response, and population density.

What is the role of the digital twin technology?

  • Test and simulate real-world scenarios: Digital twins can use data to mimic future events, which is critical to anticipate failures, inefficiencies, and high costs. For instance, the digital twin of a steel bridge in Amsterdam assessed its ability to sustain several forces that pedestrians could apply to it so that engineers could build the infrastructure, avoiding any uncertainties.

  • Monitor and predict issues: Digital twins allow one to get a complete picture of critical elements of products, assets, systems, or processes through several sensors. This data allows for the virtual monitoring of facilities and physical objects, reducing the workforce needed to conduct physical checks. The digital twin assists in triggering alerts for issues before they occur by predicting potential problems so that organizations can take timely corrective actions. For instance, a motorcycle manufacturer can use sensors on their bikes that create a digital twin to flag a potential breakdown of a part so manufacturers can build the replacement in time.

  • Optimize performance: Using digital twins helps provide insights and data that organizations can use to optimize all performance areas for a product, facility, or process to avoid failure, ensure total efficiency, minimize downtime, and maintain low costs. L&T Technology states that using digital twins can help increase revenue by 10%, decrease time to market by 50%, and enhance product quality by 25%.

Digital twin technology examples

  • Aerospace: Aerospace engineers can use digital twins to simulate aircraft performance, predict maintenance requirements and optimize fuel consumption. For instance, Rolls Royce uses digital twins to avoid reliance on probability-based maintenance methods for its aircraft engines. Sensors attached to engines and satellite connectivity allow real-time data collection to track operations and predict maintenance to reduce downtime and ensure reliability.

  • Healthcare: The healthcare industry benefits from digital twins by using them to replicate hospitals and healthcare facilities. They can also create virtual replicas of organs to monitor health data, predict health conditions and stimulate responses to health treatments. Phillips is focused on building leading healthcare technology and has created HeartModel, a clinical application that mimics a patient's heart through a 3D model based on 2D ultrasound imaging.

  • Manufacturing: In the manufacturing space, digital twins can optimize production processes, reduce downtime and test the feasibility of products before manufacturers produce them. For instance, Unilever created digital twins for its factories where sensors relay data from machines to simulate complex situations, identify optimal materials usage, and eliminate low-quality products.

  • Energy: Energy project plans can be supported by using digital twin technology. These digital twins can help optimize performance and asset lifecycles for solar projects, wind farms, and refining facilities. General Electric created a ‘Digital Wind Farm’ to virtually represent a model of a wind farm to analyze interactions of the machines with the landscape to design turbines with higher efficiency.

  • Transportation: Digital twins can provide traffic flow predictions, route optimizations, and road maintenance needs. For instance, The Los Angeles Department of Transportation collaborated with the Open Mobility Foundation to create a digital model of the city’s transportation infrastructure to track movements of micro-mobility transportation like bicycles and e-scooters and other transportation options like ride-sharing and carpools.

Which companies are using digital twins?

  • General Electric: GE uses digital twin technology across its sectors of energy, air and locomotive transportation, and health to forecast the performance of its assets, like jet engines and wind turbines, over their lifespan. In one case, GE created a digital twin for its GE90 engine to maintain its blades, which are prone to erosion.

  • Shell: Digital twins help Shell optimize the performance of its oil and gas refineries by collecting data from multiple sources and leveraging AI and ML to make better decisions, optimize asset performance and gain a competitive advantage. Shell’s Nyhamna Dynamic Digital Twin is a dynamic virtual replica of a physical gas facility that the company uses to simulate situations to optimize the performance of its real-world counterpart.

  • NASA: NASA conceptualized the idea of a digital twin when it created a ‘living model’ of the Apollo mission in the 1960s. This technology helped NASA engineers and astronauts to detect malfunctions and save the spacecraft during the Apollo 13 mission. Today NASA continues to use digital twins to simulate spacecraft performance, predict maintenance issues and build next-generation vehicles and aircrafts.

  • Siemens: Digital twins at Seimens cover the entire lifecycle of assets, including design, production, operations, and maintenance. The company uses digital twins to build virtual models of trains, machinery, and systems like chemical plants and electricity grids to speed up designing and improve performance and power.

  • Microsoft: While Microsoft provides its Azure Digital Twins technology for clients to build digital twins, it has also implemented initiatives within its own organization. In partnership with Microsoft Digital and Microsoft Azure, Microsoft's real estate team has launched a smart buildings project that uses digital twin technology to detect employee usage and enable facility management. The virtual real estate twin uses motion and occupancy sensors to analyze and enhance productivity and efficiency in the building through aspects like optimization of energy usage and building navigation assistance, among others.

Conclusion

Digital twin technology is transforming operations in asset-focused industries by enabling the creation of virtual simulations of physical objects or systems continuously updated with real-time data. These systems leverage IoT, AI, and simulations to predict performance, allow preventive maintenance, and optimize aspects of products, assets, systems, or processes. The applications of digital twins are spreading to a range of industries like manufacturing, aerospace, healthcare, energy, and transportation. Technology-driven companies like General Electric, Shell, NASA, Siemens, and Microsoft utilize digital twins to enhance their operations, improve efficiency, and make informed decisions, proving utility for organizations that aim to follow in their footsteps.

Are you a company looking to build a digital twin for a product, service, system, or process? We can help optimize your operations by building a digital twin in the metaverse. Get in touch with us!


30‏/06‏/2023

Martin Petkov

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Copyright ©️ 2023

Landvault · Wam Group

All rights reserved

Company

We build infrastructure for the 3D internet,
to create a richer, fairer internet.

Copyright ©️ 2023 · Landvault · Wam Group · All rights reserved

Company

We build infrastructure for the 3D internet,
to create a richer, fairer internet.

Copyright ©️ 2023 · Landvault · Wam Group · All rights reserved

Company