What are Digital Twins and How Companies are Using Them to Develop Products
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Although we’re still in the nascent stages of the metaverse, or the next generation of the internet, it’s certain that digital twins are a significant innovation of the century and have the potential to power the next phase of business disruption and innovation.
The metaverse has been making a lot of headlines ever since American writer Neal Stephenson coined the term in his 1992 novel Snow Crash. Lately, the focus has shifted to virtual reality (VR) gaming and social interactions within the user version of the phenomenon. However, its legacy, and often ignored, variants – the enterprise and industrial metaverses – are already being leveraged to assess future scenarios in markets like manufacturing, retail, aerospace, and transportation and logistics.
While the industrial metaverse is still evolving, and the advanced technologies that power it, one has already made a prominent mark: digital twins. With a digital twin – a real-time digitized twin of a physical object – organizations acquire a simulation in real-time to help them better manage their workflows while generating data to drive performance.
To give you a basic idea of how this technology is taking the world by storm: the global digital twin market is expected to reach $106.26 billion by the end of 2028 alone. Global IT services & consulting firm Accenture predicts that digital twins will be one of the top five tech trends that everyone should be ready for in 2023.
The Birth of Digital Twins
Digital twins are an interesting phenomenon and one of the hottest topics in the tech world right now. But what are they? And how are companies using them to develop products?
Digital twins are digital copies of physical objects, systems, or processes. They leverage technologies like artificial intelligence (AI), virtual and augmented reality (VR/AR), the internet of things (IoT), edge computing, fog computing, and the metaverse to create an accurate representation of the real world.
These copies can then be leveraged to experiment with and modify variables to study the effect on the real-world object it is being twinned with – at a small fraction of the expense of conducting experiments in the physical world.
The concept of digital twins was first familiarized in David Gelernter’s 1991 book ‘Mirror Worlds.’ Following the publicity of the book, Michael Grieves of the Florida Institute of Technology became the first person to apply the phenomenon to manufacturing. It was only in 2002 when Grieves moved to the University of Michigan and introduced the phenomenon at a Society of Manufacturing Engineers conference in Troy, Michigan.
In any case, it was NASA who first adopted the digital twin phenomenon. In a 2010 Roadmap Report, John Vickers – the principal technologist for the Space Technology Mission Directorate at NASA Headquarters – gave the phenomenon its name. Vickers also serves as the senior leader for advanced and in-space manufacturing at NASA’s Marshall Space Flight Center. NASA used the concept to build digital simulations of space capsules and spacecraft for testing.
By 2017, the concept of digital twins had already started gaining attention from companies across the globe. In the same year, Gartner named it as one of the hottest strategic technology trends. Since then, the technology has been leveraged in multiple applications and processes.
Digital twins offer numerous advantages for product-based companies and consumers. They can help mitigate costs, accelerate time to market, aid design optimization, and speed up the company’s response to new user demands. They can also give rise to new revenue streams, including remote maintenance, technical support, and “as a service” business models.
Based on the experience of companies that have already integrated the technology into their operations, the digital twin technology is expected to drive a revenue increase of up to 10% and improve quality by up to 25%, according to McKinsey & Company. Moreover, the study indicated that the technology is also expected to accelerate time to market by almost 50%. Put simply, the digital twin technology is becoming a significant industry. Studies suggest that the global market for digital twins in Europe alone will reach €7 billion by the end of 2025, with a CAGR between 30% and 45%.
Digital Twins System Architecture
Digital twins can be used for a variety of purposes, from product development and quality control to predictive maintenance and asset management. In each case, the digital twin can provide valuable insights that would not be possible with a physical object alone.
The key components of a digital twin system are:
1. Sensors: These are used to collect data about the physical object, system, or process being replicated. The data can come from a variety of sources, including sensors embedded in the object itself, external sensors placed around the object, or even manual input from humans.
2. Data Processing: This is where the data collected by the sensors is processed and converted into useful information. This step may involve cleaning and filtering the data, as well as applying statistical or machine learning algorithms to it.
3. Visualization: The processed data is then visualized in some form, typically using 3D graphics. This step allows humans to interact with and understand the data more easily.
4. Feedback Loop: The final step is to give feedback on the insights gained from the digital twin back into the physical world. This feedback loop can be used to improve the design of products, optimize manufacturing processes, or even predict failures before they happen.
Benefits of Digital Twin Technology
Industrial organizations are beginning to scratch the surface of digital twin technology. Here’s a rundown of potential benefits across multiple applications.
Digital Twins in Practice
Digital twins have a wide range of potential applications, from helping companies design better products to aiding in the maintenance of complex machinery. The promise of the digital twin concept is that it improves the physical object it is being twinned with through data insights and endless opportunities to trigger changes in simulation – both reactive and proactive.
Until now, the expense and complexity of the concept has been a challenge for many companies. However, that’s changing, with companies such as Nokia, Unilever PLC, and even supermarkets leading the way. In the future, digital twins could even be used to create entire digital worlds that mirror the real world.
That being said, let’s look at how these companies are using digital twins to develop products.
Automotive
Automotive OEMs, for example, have used the digital twin technology to increasingly develop their autonomous driving systems in virtual environments. They are leveraging the technology to build concept configurator for early phase development.
The training of ML algorithms in a virtual, simulated environment is safer and much more affordable than real-world tests. Additionally, automakers can run multiple simulations in parallel to speed up the testing process by over 10,000 times. This can help automakers improve the accuracy of their simulations and determine limitations in the virtual test database.
Telecommunication
Designed to introduce Industry 4.0 phenomena for the manufacturing of Nokia 4G and 5G base stations in Oulu, Finland, the company used the digital twin technology along with automation and other digital solutions to increase productivity by almost 30% in a year and mitigate manufacturing defects by 50% over four years.
The “factory of future” in Oulu produces 1,000 Nokia 4G and 5G base stations per day for secure and reliable connectivity of all assets inside and outside of the factory, IoT analytics, and a real-time digital twin of operations data. By leveraging the company’s private wireless networks, they were able to achieve annual cost savings of millions of euros.
Industrial Manufacturing
In industrial manufacturing, digital twin technology is leveraged to improve the production process. Companies can create visual representations of the overall production process, a real-world project, machinery, or a whole system by leveraging data generated from industrial IoT solutions, IoT sensors, and manufacturing tools.
A good example of digital twin technology in consumer goods manufacturing is that of Unilever PLC. The company is leveraging digital twins to bring more efficiency and flexibility to the overall production process.
Put simply, Unilever PLC has created virtual models of its manufacturing hubs. At each factory unit, the IoT sensors feed data like temperature and motor speed into the cloud, while an IoT digital twin stimulates what-if scenarios to determine the best operational scenarios through ML algorithms and advanced data analytics. This helps the company use materials and equipment elements more accurately, thereby eliminating waste from products that don’t meet their quality standards.
At present, Unilever PLC is using eight digital twins across Asia, North America, Latin America, and Europe.
Ecommerce & Retail
French retailer Intermarché built a digital twin of a physical store based on data generated from IoT-powered shelves and sales systems. This has helped store managers to manage inventory and test the capability of various store layouts easily and effectively.
With digital twins, retailers can identify limitations, product shortages, and demand gaps in seconds. Moreover, they can achieve proper product placements, restock goods, and create targeted ads to generate more sales and reduce wastages.
A study by Boston Consulting Group indicated that digital twin technology can help retailers and store managers reduce capital expenditures by up to 10%, cut down excess inventory by almost 5%, and make EBITDA (earnings before interest, taxes, depreciation and amortization) improvements between 1% and 3%. More importantly, they can also transform their working environment and business processes for better opportunities.
How Digital Twins Can Accelerate the Transformation of the Healthcare Industry
Digital twins are becoming an increasingly popular tool in the healthcare industry, as they offer a number of advantages and benefits.
The healthcare industry is using digital twins to develop new drugs and medical devices. Digital twins can be used to test the efficacy of new treatments and predict how patients will respond to them. This information can help doctors choose the best course of treatment for their patients.
For example, Medtronic has developed a mapping system called CardioInsight, which gathers and combines the electronic data of the patient body surface with heart-torse anatomical data and gives a 3D map of heart’s electrical activity. This example of diagnostic treatment has also received FDA approval.
That being said, we’ll explore two of the most important use cases of digital twins in healthcare, for 2023 and beyond.
Disease Modeling
Digital twins are digital representations of real-world objects or systems. In healthcare, they can be used to model diseases and predict how they will progress.
Digital twins can help healthcare organizations to better understand diseases and develop more effective treatments. For example, by modeling the progression of a disease, digital twins can help to identify early warning signs and potential interventions.
They can also be used to test new treatments and medicines before they are rolled out to patients.
Medicine & Device Development
Digital twins can provide a way to test new medicines and devices in a virtual environment before they are trialed on humans. This can help to speed up the development process and ensure that new treatments are safe and effective before they are made available to patients.
Moreover, they can also be used to model the human body and disease processes, which can help researchers to develop new medicines and treatments. By understanding how diseases progress and how the human body responds to different treatments, researchers can develop more targeted and effective therapies.
Digital twins can also be used to personalize medicine and treatments for individual patients. By creating a digital twin of a patient, doctors can test different treatments and see how the patient would respond, without having to put them through invasive or risky procedures. This could enable doctors to find the best possible treatment for each individual patient, based on their unique characteristics.
Overall, digital twins offer a powerful tool for healthcare organizations, which can be used in a variety of ways to improve patient care. By utilizing digital twins in the development of new medicines and devices, healthcare organizations can speed up the process of bringing new treatments to market, whilst also ensuring that they are safe and effective.
Starting on Your Digital Twin Journey
Starting on a digital twin journey can look intimidating and challenging in the beginning, given the wide array of its use cases spanning multiple industries and corporate landscapes, including manufacturing, design customization, automotive development, R&D, and through-life support amongst others.
This adaptability can also be a boon, however, as it enables industrial companies to start small and expand the scope, efficiency, customization, organizational capacity and competency, and value-chain coverage of their digital twin projects.
The experience of industrial companies that have leveraged digital twin technology in their operating models leads to a few basic rules that can significantly increase your chances of success.
#Rule 1: Define Your Project Goals
#Rule 2: Identify Your Strengths
#Rule 3: Plan a Step-by-Step, Agile Implementation
By seeking out perspectives on the best practices and future trends of digital twin technology, your organization will be able to reap the advantages of digital twins in the best possible way. Are you ready?
The Future of Digital Twin Technology
A significant change to legacy operational models is certainly happening. A digital revolution is underway in industries that is changing operational models innovatively and radically, requiring both physical and digital versions of assets, manufacturing hubs, equipment, and processes.
Digital twins are a major part of that reinvention.
The future of digital twin technology is endless since it leverages huge amounts of cognitive power and other advanced technologies such as NLP (Natural Language Processing), object visual recognition, acoustic analytics, IoT, advanced analytics, and signal processing. This means that digital twins are constantly feeding new learning skills and capabilities to generate the insights required to improve processes and make products better.
Digital twins have endless potential applications, and it is only a matter of time before they become more widespread and sophisticated. As technology advances, so will the capabilities of digital twins.