The concept of digital twinning has been around for quite some time, yet as its primary enablers, data analytics and IoT, are reaching maturity, digital twin applications are finally beginning to be used beyond manufacturing. As enterprises are increasingly harnessing the power of virtual prototyping, the trend is obvious. The only thing that remains unclear is how exactly digital twinning works in practice.
IoT-Powered Digital Twins
Digital twinning is the use of technologies for mirroring physical systems through digital simulation. In essence, a digital twin is a piece of advanced software that operates on real-time data pulled from physical objects. This is done in order to produce simulations and predictions for the optimization of components, assets, networks, processes, and systems.
It is through the continuous incorporation of up-to-date information that digital twin technology delivers the most value. Similarly to virtual prototypes, it establishes a link between the digital and physical spheres, but one that is persistently updated to reflect the current state of being.
By capturing data from smart assets in real time and converting it into insights, digital twins help prevent failures and find solutions, which aids in generation of effective business policies and decision making. In the business context, this means reduced downtime, lower production and maintenance costs, enhanced customer service, and faster time to market.
Through the smooth integration of continuous data feeds, digital twins provide businesses with a current view of their products and processes, which enables businesses to be proactive, predictive, and cost-efficient. To deliver those benefits, virtual simulations need data, and smart IoT sensors bring it to them, in real time.
The Internet of Things provides organizations with access to information about the physical world; digital twins leverage that information, allowing it to be immediately analyzed, optimized and tested. Bringing those two technologies together are digital threads — continuous, seamless data flows enabling traceability throughout an asset’s lifespan.
By 2022, 75% of IoT platforms are expected to contain some form of digital twinning.
Digital twins reduce the complexity of IoT ecosystems, as they integrate enormous datasets gathered by smart sensors (such as connected lighting, cameras, thermostats, power meters) and map them into digital replicas that are easier to analyze, measure and comprehend. The pace of adoption of the technology is speeding up, and current research confirms that. According to Gartner, by 2021, 75% of organizations implementing IoT already use digital twins or plan to do so within a year, expecting 10% improvement in their efficiency. Markets and Markets predict that by 2025, the digital twin market is estimated to grow to $35.8 billion by 2025, at a CAGR of 37.8% since 2019.
Digital twin conceptual architecture
IoT Digital Twin Use Cases
Until recently, engineering-oriented, asset-heavy industries such as manufacturing and product design have been the main beneficiaries of digital twin technology. Nevertheless, as the availability of enabling technologies such as IoT, AI and cloud computing is increasing, new applications of digital twinning are emerging across other verticals.
While automotive companies are still racing to make self-driving technology commercially viable, most of them have already adopted IoT-powered digital twins to capture the behavioral and operational data from sensor-studded cars. Automotive engineers build digital models of vehicles to identify possible failures and glitches in design and make improvements in car safety, efficiency, and innovation, all before the actual production.
Leading this innovative drive is Tesla, which creates a digital twin of every model, but other manufacturers are keeping pace. Nissan, for example, is leveraging real-time virtual prototypes to pinpoint the cause of battery leaks, reduce pallet volumes, and optimize rack space storage, among others. Similarly, Mercedes’ plants use digital mock-ups to simulate the entire production process for greater efficiency and flexibility, making it possible to respond to customer demands faster.
Another exciting application of digital twins in the automotive context is speed racing, where virtual simulators ideally mimic the track experience to provide engineers with in-depth insights on vehicle design and aerodynamics. This knowledge consequently translates into improved driver safety and a thrilling sports spectacle for the viewers.
The manufacturing industry is where the most advanced uses of digital twinning can be found. The technology delivers real-time, 360-degree visibility into products and processes, from the drawing board right to the final assembly. It empowers manufacturers to build and test new, advanced concepts without shutting down production lines and impacting lead times.
Digital product definitions open the floodgates for experimentation, providing endless possibilities to analyze real-world product applications without incurring the immense costs associated with traditional R&D operations. Powerful simulations of the production process guarantee that the achieved output will echo the initial projections.
One classic example of the benefits that digital twin applications bring to heavy industries is that of aerospace engineering. Take Boeing, for instance. The company engineers are conducting digital simulations on various aircraft components to assess their durability, longevity, and reliability. This helps the company ensure the highest standards of safety for passengers and crew. Thanks to digital twinning, Boeing can predict how particular parts will perform, and forecast — and avoid — the potential risks of engine failure.
Digital twinning is also driving robust transformation in smart cities. City planners and authorities install meters and sensors to monitor and track traffic levels, helping them better understand occupancy, environmental conditions, energy consumption, public safety, and other aspects of the urban ecosystem. Virtual simulations allow them to generate parallel versions of their cities to test policies and visions for more sustainable, citizen-friendly, and profitable municipalities.
Singapore is famously the first city to tap into abundant data to improve the quality of life for its citizens. The metropolis incorporates simulated environments into its development strategy to support healthier, stronger, and safer communities. Other cities that have followed in its footsteps include Zurich, Copenhagen, Jakarta, Melbourne, Cape Town and Shenzhen, to name just a few. Many more municipalities are also dipping their toes in virtual prototyping to resolve the challenges of urbanization. It’s estimated that by 2025, the number of smart cities worldwide will reach 500.
By providing a sandbox environment for testing new architecture design concepts, virtual prototyping holds great promise for the real estate industry to cut construction time and costs and gain greater visibility into how tenants use their building. Complex simulations of buildings and surrounding areas enable architects and developers to design assets that are optimized in terms of energy efficiency, environmental quality, and tenant expectations.
This is not the only benefit that digital twins can deliver to the real estate market. Construction and engineering businesses may also use predictive capabilities of digital twinning to facilitate progress monitoring, and support resource planning and logistics. All of these applications of digital twin technology bring sizable reductions in operating costs to real estate businesses and may help them increase the value of their property assets.
Digital twinning can simulate upcoming events and suggest possible scenarios for the future, enabling diverse applications in the logistics sector.
Logistic companies are already taking advantage of IoT sensors to track shipments or, as in the case of Amazon, validate delivery methods, including autonomous delivery. Now, they may go a step further with IoT-powered digital twins, creating virtual simulations to improve volume utilization and devise more efficient and sustainable packaging solutions. In distribution centers and warehouses, information harvested from machinery can serve as input for predictive models that can forecast and prevent breakdowns and downtime.
An IoT digital twin can also help with warehouse planning, configuration, management, and continuous optimization. One of the companies making extensive use of this application is DHL. The global leader in logistics leverages real-time operational data to continuously evaluate the potential impact of changes on facility layout, equipment, staff productivity, and processes.
The retail industry is rich in consumer data that can be pulled from PoS systems, mobile devices, in-store beacons, and other sources. With digital twinning, this information can be easily turned into comprehensive virtual representations of stores.
In-store, digital replicas allow retailers to monitor and test the optimal placement of products and manage their distribution to match the customers’ patterns of interest. Using digital twins, retail companies can also get a glimpse of the entire product lifecycle, from design through to sale. This knowledge enables retailers to prevent stockouts and reduce waste. Finally, e-commerce and retail organizations employ digital twins to build sophisticated models of consumer behavior that help them create customer-centric, personalized experiences. The detailed consumer information harvested from a variety of touchpoints, including purchase history, website visits and social media engagement, can be used later to improve the efficacy of advertising and marketing campaigns.
Technology plays a transformative role in medicine, improving treatment outcomes and increasing patient comfort. Digital twinning is now part of that. As the connected-healthcare trend is accelerating, virtual models can be used to produce data-driven strategies that support extremely complex medical environments and enhance safety, accessibility, and efficiency of treatment.
Here are a few examples of popular digital twin use cases in healthcare. Analytics consultants can use digital twins to model new hospitals or remodel existing facilities to discover the optimum bed arrangement, staffing distribution, and floor plan. Virtual prototyping can combine data collected from wearables, patient portals and mobile devices to create a lifelong record of a patient’s health. Such a model will facilitate outcome prediction, chronic disease management, and hyper-personalized treatment. Medical device manufacturers can also benefit from digital twinning, using virtual models to create advanced, affordable orthopedic devices, while bypassing the costly development of physical prototypes.
Digital twins are used to great effect in the data-rich utility sector, where they offer a consolidated view of physical grids and processes. They replace or enhance traditional information systems and manual operations with a single, spatially enabled platform. As model simulations continuously learn and update themselves, they help eliminate data inconsistencies and build a reliable, data-driven foundation for predictive utility management.
The transparency of dynamic models aids utility providers in improving asset management, detecting anomalies, and preventing failures. Through those enhancements, electric, gas, water and other utility companies can also alleviate the social and economic impacts of service outages or failures.
An interesting application of digital twins within the utility sector comes from Sydney Water. Pursuing its vision for integrated water services, the Australian water utility company employs digital simulation to increase the accuracy of hydraulic models for more efficient supply planning and proactive identification of issues.
As businesses try to escape the commoditization trap, digital twinning provides them with the opportunity to build market differentiation with new, hyper-personalized products and services. Real-time simulations and predictions allow organizations across industries to use a proactive, data-driven approach to preventing failures, refining product quality, streamlining processes and bringing value to their markets ahead of competitors.
Since digital twins are entering mainstream use, this technology now has the opportunity to evolve into a tangible and meaningful construct that forward-looking companies may readily employ to improve their business outcomes.