- Overlooked in the rise of digital twins are the ways it is changing how people work together
- The technology is yielding big payoffs, including up to 30% gains in labor efficiency, according to Deloitte
- Digital twin applications are capable of modeling business processes, not just physical products
Singapore is creating a digital clone of itself.
“Virtual Singapore” is a data-rich replica of the entire Southeast Asian island nation. The $73 million project pulls information from millions of devices that measure everything from traffic flows to air quality, and energy usage. Still more devices control rail systems, traffic lights and street lamps. All this data is used to create a “digital twin” of the city-state that enables officials to better monitor city operations and simulate the effects of big trends such as population growth or climate change.
Singapore’s digital twin applies predictive analytics to massive data feeds from IoT devices and systems, creating a virtual replica that performs very much like the real-life object or system that it models.
Automakers and other manufacturers, utilities and healthcare companies are among the industries embracing the potential of digital twin technology. Tesla maintains a digital twin of every vehicle it makes. Nestle uses digital twins to monitor performance of its production lines. Airbus is developing digital twin software that will create a virtual model of its shop floor.
Somewhat overlooked in the rise of digital twin technology are the ways it is changing how people work together. Digital twins are empowering engineers to design products more efficiently, automate repetitive processes such as quality control and inspections (freeing workers to devote time and energy to higher-value tasks), and improving how teams communicate and collaborate, sharing information visually among both technical and non-technical team members.
By predicting how a product might behave under a variety of conditions, digital twins can also enhance the ability of operators to run and maintain complex systems such as jet engines, offshore wind farms and smart factories, providing real-time insights into their performance.
“The digital twin is impacting all areas of the product life cycle, and it starts with design,” says Thomas Ohnemus, vice president of solution marketing for digital supply chain management at SAP. “You can simulate a lot of characteristics before the product even gets built.”
Modeling with digital twins
The explosion in the number of IoT-connected devices— there will be 150 billion on the planet by 2030, according to IHS Markit research—has been a key driver of digital-twin adoption. Nearly half of all companies implementing IoT are already using, or plan to use, digital twins this year, according to Gartner research. By 2021, they will help those companies improve their efficiency by 10%, the firm predicts.
Companies across the spectrum are pouring money into developing digital-twin applications. The global market for digital twin technology is expected to grow 38% annually, reaching $16 billion by 2023, according to Deloitte.
The technology is already yielding significant payoffs, including a 15% to 30% gain in labor efficiency, according to Deloitte. “If I’m 30% more efficient, I have less work that I’m doing and I can actually create more new products,” says Brian Meeker, principal in product strategy and lifecycle management at Deloitte.
NASA developed the concept behind digital twins in the early days of space exploration, when engineers created physical twins of spacecraft and used them to test, monitor and repair systems during live missions. Today, NASA designers rely on the technology to create virtual models of equipment, which can be tested for optimal performance, stability and functionality before spending any money on physical prototypes.
Car manufacturers are using digital twins to conduct virtual tests on new car designs. Engineers can use a car’s digital twin to perform simulated crash tests to show the effects on an impact in extreme weather conditions or at high speeds. Maserati reports that the technology has cut development time for new models by 30%.
“In the past, you crashed 10 physical cars against a wall,” Ohnemus explains. “Today you do eight crash tests digitally, and at the end you run maybe one or two physical tests, and those two are already the optimized version of the model.”
Using a digital twin can also help streamline the design process by making it easier for engineers, product managers, marketers, supply-chain experts and others to participate at every stage. Customer feedback can be easily included in the design process. Designers can create virtual models of different versions of a product, and then test them with customers to find which one best satisfies their tastes and needs.
Once a product hits the market, data on customer complaints, failure rates and overall performance can be fed back into the digital twin to identify problems and improve designs for the next generation of the product.
“It’s about taking a more connected, open view of how you’re designing and developing products and improving them over time to improve the customer experience,” says Jeff Hojlo, program director of product innovation strategies at IDC.
Collaboration gets virtual
Digital-twin technology makes collaboration easier. For one thing, by conveying information visually rather than through spreadsheets of data or specialized terminology, it allows technical and business units to work together more effectively. Suppliers, shippers and other parts of the logistics chain “can become innovation partners and work with you as part of the team,” Hojlo says.
The technology also erases distance between business units. With physical prototypes, engineers have to be in the same room. “If you have different teams around the globe, they can share a digital model and work together on it,” says Ohnemus.
Working with digital twins also cuts down on inefficient meetings and email chains. Far-flung engineering teams can make changes directly in the model without a lengthy back and forth. Those efficiencies, in turn, help break down stubborn silos.
“With digital twins, [engineers] can work with marketing, sales, even with the service guys in the engineering phase,” says Ohnemus. “You can ask, ‘If we design the product this way, what is the best way to service it?’”
In healthcare, digital-twin technology is being developed to enable collaborative surgery. HeartModel software, developed by Philips, creates a virtual model of a patient’s heart, and a cardiovascular specialist in a remote location can use it to guide another doctor through complex surgical procedures. Some experts envision the creation of a “digital patient” that will allow a physician to monitor and treat a patient remotely through data from sensors implanted throughout the human body.
Next-gen digital twins: process simulators
For the most part, digital twins today are created for physical products. But the next evolutionary stage of the technology, experts say, is a “process twin.” Such a virtual model could be used to consider the design, development and operation of business processes such as energy consumption or worker productivity.
“Virtual Singapore” is a hint of what’s possible on that front. If the data from thousands of disparate devices and systems can create a digital twin of a sprawling metropolis, why couldn’t a large corporation do the same and bring data from facilities, supply chains and workflows into a single virtual model? “You can take almost a mission-control approach to operations,” Hojlo says.
For the moment, the promise of digital twins for workers is a bit simpler: As Ohnemus says, they will “take a lot of heavy work away from human beings and make their lives easier.”