A child creates his avatar in FITUR. The HELIXA Experience Center is the technical and artistic installation of the FITUR exhibition center. This will be the first opportunity for visitors to create their own avatar in real time. This avatar is a personalized, surreal, 3D #seriezero digital twin that they can use to interact across digital platforms and the metaverse.
Guillermo Gutierrez Carrascal | Light Rocket | Getty Images
The concept of a digital twin—a digital representation of a physical system, product, or process that serves as an indistinguishable counterpart for purposes such as simulation, testing, monitoring, and maintenance—has been around for some time. But there are signs that the time has come for the concept to be widely adopted to support business applications.
“With the rapid adoption of digital twins, we are seeing the emergence of two classes of practical applications: industry use cases that solve very specific challenges, and industry agnostic use cases that contribute to broader strategy and decision making,” said Tata Consultancy Services Chief Future J. Frank Diana.
Like artificial intelligence a few years ago, digital twin technology has moved from a highly specific application to a broad management best practice, Diana said.
Matt Barrington, head of emerging technologies at consulting firm EY Americas, said: “With the deeper and more contextual insights that digital twins provide, we can better understand our products, processes and systems, and gain more insight into our models. Have confidence.”
“For example, this gives more organizations the confidence to experiment with access-based service models for complex products or new data-based services,” such as twin-based insurance policies for smart buildings, Barrington said. “Moving forward in a more dynamic, ecosystem-oriented market, we want all companies to support and rely on [on] Digital twins run most aspects of their business intelligently,” he said.
Real-time data comes to life
Companies are using virtual product development twins to more efficiently speed up design and development cycles, Barrington said. “Digital twins take our existing models of products, processes and systems and bring them to life in real-time with real-world data,” he said.
One practical application of digital twins in TCS is guiding a company’s return-to-office strategy late in the pandemic, Diana said. “In order to reopen effectively, we need to know the answers to questions like how many [workers] May be infected? Who should we test and when? What should be the capacity of our isolation facility? “He said.
To answer these questions, TCS created a digital twin environment with a novel machine-processable “local model” with the primary goal of predicting and controlling the spread of Covid. “Digital twins can be used as quantitative aids to interpret current environmental conditions and assist in decision-making, allowing our employees to return to the office safely and efficiently,” said Diana.
Diana said digital twins are also replacing historical data-driven models for business strategy. “These legacy strategic platforms lack the ability to address the deviations and disruptions that are becoming increasingly common in the post-Covid world,” he said.
Along with artificial intelligence, Diana said, organizations are using digital twins to help envision, experiment and execute business decisions through simulators that represent key business entities, interrelationships and external forces such as competitors or natural disasters.
In the life sciences, digital twins are being used to create twins of human organs, enabling new approaches to medical research and care, Diana said. Instead of relying on animal testing, pharmaceutical and cosmetic companies could use twins to test how to deliver new drugs or products to human skin in cyberspace, he said. Researchers could use the digital heart to find new surgical techniques or cures for heart disease.
Digital twins are also being used in smart city initiatives, Diana said. Los Angeles, for example, is employing digital twins to simulate traffic movements and activities, such as ride-sharing and drones, to better plan its mobility infrastructure.
Another possible application is in environmental, social and governance initiatives. Dan Versace, ESG business services research analyst at research firm International Data Corp, said the technology “uses huge datasets of historical weather, travel and physical infrastructure data to create a digital twin of any physical location”. Through the use of artificial intelligence and machine learning, the digital twin can perform in-depth analysis to provide users with an exhaustive, scenario-based assessment of environmental conditions, Versace said.
“If applied correctly, this technology could provide insight into the growing physical risk of climate-related natural hazards,” Versace said. “Over the next year, the technology’s capabilities will only grow, with some organizations claiming they not only Being able to explain the immediate risks organizations face from climate change, but also being able to explain the impact these disasters will have on their customers and value chain.”
Versace said this will allow companies to develop resilience planning and mediation strategies long before they are needed, without facing any significant risk.
“We will see rapid adoption of digital twins in many different industries in 2023,” Diana said. “The volatility and uncertainty looming this year will be the catalyst that pushes companies into rehearsing an uncertain future. Digital twins will be a key tool in rehearsing.”
Digital twins are gaining momentum in adoption and sophistication as more organizations see positive results from early adopters, Barrington said. As digital twins become mainstream, EY predicts two major trends. One is hyper-personalization, which uses twins to better tailor products, services and experiences to increase customer loyalty and value.
Another is the dynamic supply chain. “As more twins of critical assets and processes come online, leaders will leverage digital twins to not only model and simulate their supply chains, but to optimize and automate dynamic and intelligent supply chain models—all powered by digital twins. Well planned,” Barrington said. “Many leaders have learned from the recent pandemic that static linear supply chains are not enough moving forward, and digital twins are one of the best ways to mitigate risk.”