Digital Twins in 2021: 15 Amazing Examples

The concept of digital twin is not new. The technology has been around since the 1960s. NASA has been physically creating duplicate systems for its various space missions at ground level, to test its equipment in a virtual environment. An example of this is Apollo 13, for which a digital twin was developed by NASA to assess and simulate conditions on board.

In the recent past, digital twin has become one of the most promising technological trends. It is estimated that that the global Digital Twin technology will reach $48.2 billion by 2026, from $3.1 billion in 2020 and estimated to grow at a rate of 58% between 2021 and 2026

A digital twin is a digital representation of a physical object, process, or service. A digital twin can be a digital replica of an object in the physical world, such as a jet engine, wind farms, or even larger items such as buildings, or whole cities. This twin technology is used to replicate processes to collect data and predict the performance.

With the rising internet penetration coupled with the proliferation of smartphones and the advent of advanced technologies such as VR, AR, AI, machine language, deep learning, and blockchain is driving the market growth of Digital Twins as a technology. It is helping to reduce the time to market, increase operational efficiency, and improve product lifecycle for various end-use segments such as healthcare, automotive, and aerospace.

"By incorporating digital twin technology with our wearables that are equipped with embedded AI, we're able to build our products to their fullest potential, pioneering this new innovative method of preventative safety."

- Ognjen (Ogi) Grba, CEO – Connect Up Technologies

Below are some amazing examples of how the digital twin technology is being used:

Use Case 1 – Automotive

Developing new cars mostly takes place in a virtual setting. Digital twins are used in the automobile industry to create the virtual model of a connected vehicle. Automotive companies use the technology to design the ideal automotive product even before production starts. They simulate/analyse the production phase and the problems that might occur once the vehicle hits the roads.

Use Case 2 – Autonomous Vehicles

Self-driving cars contain numerous sensors that collect data regarding the vehicle itself and the environment of the car. Due to the liability questions that surround autonomous vehicles, creating a digital twin of a car and testing every aspect of the vehicles is helping companies ensure unexpected damage/injuries will be minimized.

Use Case 3 - Quality Management

Continuous monitoring of product data has clear advantages for quality management over random inspection. The digital twin can monitor and model every part of the production process to identify where quality issues may occur. It can also analyze the composition of the product being created to ascertain whether there were better materials or production processes that could have been used.

Use Case 4 - System Planning/Virtual Start-up

The analysis of historical data from similar systems within a manufacturing plant makes it possible to predict the performance of a system that has not yet been constructed. The digital twin allows to use this information to model different scenarios for the new equipment and identify areas where new plants can be improved over previous production systems.

Use Case 5 - Logistics Planning

Digital twins can help optimize supply chain. It allows to gain a much clearer view of materials usage and provide the opportunity to automate the replenishment process. Where lean or agile manufacturing processes are used (just-in-time or just-in-sequence production), can result in significant increase in efficiency.

Use Case 6 - Product Development

Virtual simulations help with development of new products and product variants. Data collected from the use of a product can also help to develop and improve version control. The digital twin allows to blend data from production systems with data to other enterprise applications such as ERP, CRM, or CEM systems so that real feedback is included on the product use during the product re-design process.

Use Case 7 - Disaster Management

Global climate change has already resulted in a wide range of impacts across many regions and countries. Fires, floods, and droughts have become normal now. In such a scenario, digital twin is being used to build smarter infrastructure like dams, utility networks, emergency response plans, and zoning.

Use Case 8 - Aviation

As a digital twin is created for a new plane, simulations are run to predict the performance of various airline components over the lifecycle of the product. As a result, engineers can predict when products are expected to fail and share that information with its supply chain.

Another digital twin use case that is being explored in the airline/defence industry is to achieve a perfect cargo load balance. For example, a Boeing 737 has a maximum cargo load of 80,000 kilograms but many planes fly with less cargo than this as weight figures are calculated manually. By using IoT sensors on a digital twin, a precise and yet safe cargo load can be determined increasing cargo revenue per flight.

Use Case 9 – CPG

Makers of fast-moving consumer goods are using digital twins to enhance their operational efficiency. For example, Unilever takes data from IoT systems and feeds into the digital models of each factory. This data is then processed by algorithms which can then be used to improve the overall manufacturing process. These trained algorithms are then plugged back into the physical factory to automate the manufacturing process. Unilever has seen significant success from deploying digital twins to greatly increase the consistency in production of soaps and detergents.

Use Case 10 - Healthcare

In healthcare, digital twins of a particular patient organs allow doctors to test different care delivery approaches enabling patient-specific surgery training to prepare for complex invasive procedures. With insight created by digital twins, healthcare organizations can create innovative practices to correct the problem and minimize the possibility of any kind of risk.

Use Case 11 - Insurance

For insuring anything from any kind of risk it is important to understand the location of the risk. For example, insure a famous historical monument from risk of terrorist attack, a Digital Twin model can help to understand that which is the area from where terrorists can easily enter in the monument. Once the location is known it is easy to take protective measures.

Use Case 12 - Smart Cities

Digital Twins can help cities to become more environmentally, economically, and socially sustainable. It enables users to create models that guide their future and help provide solution to the complex issues that cities face. In case of any disaster like flood, Digital Twin provides useful information in real-time, like which areas are flooded, which infrastructure will be shut down, which hospitals could be affected and thus allowing city managers to take immediate action. There is a digital twin of Singapore

Use Case 13 - Car Racing

Digital twin technology has been deployed to refine Formula 1 car racing. In a sport where every second counts, a simulation helps the driver and the car team know what adjustments can improve performance.

Use Case 14 – Space Optimization

The virtual model of a building allows to evaluate space capacity and smartly design it, so that the building becomes more functional and convenient for occupants. This application is especially relevant for workspaces, where space allocation plays a vital role. Moreover, the Digital Twin ability to simulate various scenarios allows to easily identify and design emergency evacuation routes.

Use Case 15 - Wearables

Combining digital twin technology with wearable devices - like from Connect Up Technologies - can provide valuable data for identifying inefficiencies and recreating accidents. Connect Up Technologies combines the digital twin technology to give accurate, real time locations of the workforce and any assets that need to be located. If an accident occurs, a company can easily find where and how and use the data collected from the wearables to provide insurance adjusters with an accurate recreation of the accident.

"Digital Twins as a technology can transform the way the world functions. When we can dream and imagine of innovative and efficient ways to apply this technology, the possibilities are endless."

- Asokan Ashok, CEO – UnfoldLabs Inc

The Benefits of Using Digital Twins

Accelerated Risk Assessment and Production Time

With the help of a digital twin, companies can test and validate a product even before it comes into existence. By creating a replica of the planned production process, it enables engineers to identify any process failures before the product goes into production. Engineers can disrupt the system to synthesize unexpected scenarios, examine the system’s reaction, and identify corresponding mitigation strategies. This new capability improves risk assessment, accelerates the development of new products, and enhances the production line’s reliability.

Predictive Maintenance

Since a digital twin system’s IoT sensors generate big data in real-time, businesses can analyze their data to proactively identify any problems within the system. This ability enables businesses to schedule predictive maintenance more accurately, thus improving production line efficiency and lowering maintenance costs.

Real-time Remote Monitoring

It is often very difficult or even impossible to get a real-time, in-depth view of a large physical system. However, a digital twin can be accessed anywhere, enabling users to monitor and control the system performance remotely.

Better-Team Collaboration

Process automation and 24×7 access to system information allows technicians to focus more on inter-team collaboration, which leads to improved productivity and operational efficiency.

Better Financial Decision-Making

A virtual representation of a physical object can integrate financial data, such as the cost of materials and labor. The availability of a large amount of real-time data and advanced analytics enables businesses to make better and faster decisions about whether adjustments to a manufacturing value chain are financially sound.

Facing New Security Challenges

The faster a new type of technology spreads, the less attention tends to be paid to security at the outset. This forces companies to scramble to put out metaphorical fires when vulnerabilities are exploited, leading to the loss of time and profits.

As digital twins are usually based in the cloud and don’t require physical infrastructure, the associated security risks are somewhat lower than with other types of systems. However, the massive amounts of data being collected and utilized is drawn from numerous endpoints, each of which represents a potential area of weakness. It’s estimated that 75% of digital twins will be integrated with at least five endpoints by 2023 , and a time is coming when visualizing complex systems may require the linking of multiple digital twins.

Every time a new connection is made and more data flows between devices and the cloud, the potential risk for compromise increases. Therefore, businesses considering digital twin technology must be careful not to rush into adoption without assessing and updating current security protocols.

My Thoughts on Digital Twins in 2021

Going forward digital twins will emerge as one of the key IT tools in many industries, especially in manufacturing but will also revolutionize product development and product testing in a wide variety of areas.

Therefore, in the future almost every manufactured product could have its own digital twin if it is generating data that can be captured and analyzed. This concept is known as a `digital triplet` and will represent the next stage of evolution of the digital twin. For example, instead of Boeing having just one digital twin of a new aircraft for development purposes, the company will have a unique digital model for every aircraft it makes. These individual models can be fed information from connected sensors in real time, and AI analysis can be applied to make real time predictions about the product life cycle, predictive maintenance etc.

Going forward human beings will also have their own digital triplets, which will collect real-time information from wearables and can contain a user`s unique genetic code and using this information in theory every person on the planet could receive extremely individualized yet cost effective medical treatment. It is just a few years away !!