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Last year the world held its breath as Notre Dame Cathedral stood shrouded in flames.
After the fire was extinguished, and it was revealed that the iconic cathedral was not lost, the hard work of restoration began. Until very recently, that process would have begun with a search through dusty archival blueprints to guide the intricate repair works. But in the age of the digital twin, engineers and architects were able to consult a digital model of the French cathedral — one far more detailed and interactive than any blueprint — which allowed them to stay true to the original structure while also incorporating new innovations in design and materials.
As its name suggests, a digital twin is a virtual replica of an object, being, or system that can be continuously updated with data from its physical counterpart. Supported by an estimated 25 billion connected global sensors by 2021, digital twins will soon exist for millions of things. A jet engine, a human heart, even an entire city can all have a digital twin that mirrors the same physical and biological properties as the real thing.
The implications are profound: real-time assessments and diagnostics much more precise than currently possible; repairs literally executed in the moment; and innovation that is faster, cheaper, and more radical.
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An Innovation Game Changer
Many commentators today worry about a crisis of innovation afflicting companies and economies. Some say we’re running out of new ideas and “life-altering” innovations. Others claim that innovation is crippled by bureaucracy and regulation.
But a more basic explanation is that innovation has always been difficult. It takes time. It requires costly trial and error. And it often faces significant ethical, social, and regulatory obstacles.
Consider car manufacturing, where development time has shortened from 54 months in the 1980s yet still takes 22 months today. Or the development of new lifesaving drugs, where the journey from discovery to commercialization can last decades.
Digital twins stand to change the innovation game by enabling three critical drivers:
1. Continuous evaluation. Traditionally, most complex products could be fully analyzed, piece by piece, only twice during their lifetime — when they were created and when they were broken down at the end of their life cycle. Now that sensors can capture and continuously update the product’s digital twin throughout its lifetime, manufacturers have a live window inside the product at all times.
In manufacturing, AStar — Singapore’s Agency for Science, Technology, and Research — works with companies to equip their machine equipment with digital twins that automatically make adjustments to its operation, such as correcting a wobbling piece on a spindle. This removes the need for extensive diagnosis and repair, and can significantly reduce downtime.
Tesla takes it a step further: Every car has its own digital twin. Through sensors, the physical car continuously sends data to its digital twin. If the vehicle has a rattling door, the system will prompt you to download software that will adjust the door’s hydraulics.
As Tesla collects information about the performance and use of each vehicle, its engineers also aggregate the data to create updates that will improve the performance of that specific range of cars, a very real example of real-time innovation. This process also helps engineers and designers understand what cannot be improved with software updates alone — crucial information to make bigger innovation leaps when seeding the next version of a product.
2. Faster, cheaper prototyping. Digital twins can dramatically lessen the need for expensive tests and physical prototypes, reducing the cost and increasing the speed of innovation. The cost of developing new drugs, for example, reaches into the billions, and preclinical testing phases alone take an average of three and a half years. Oklahoma State University developed a digital twin of an aerosol drug intended to reach lung tumors. By varying parameters on the digital twin such as inhalation rate and particle size, scientists increased the number of particles reaching their target from 20% to 90%, sparing them the need to create several prototypes and shortening the testing process.
Similarly, railroad passenger coaches have traditionally needed to be tested in wind tunnels to make sure they comply with regulations and don’t get too hot or cold. Siemens paired up with Ansys, an American engineering simulation software developer, to design a digital twin of a coach to test the effect of different wind and climate conditions. The result: testing times were halved, leading to savings on equipment, manpower, and wind-tunnel rental cost. Additionally, passenger comfort was improved beyond standard requirements, and the need to test product variants was eliminated.
Applied to a system or process, digital twins can eliminate the need for physical experimentation while optimizing performance under different conditions. For example, Accenture worked with Ireland’s An Post, a public postal service, to create a digital twin of its hundreds of vehicles, delivery routes, multiple sorting centers, and different processes to evaluate the impact of new technologies and test new approaches on throughput and timeliness.
3. Innovating at the limits. When it comes to solving big human and social problems, the process of innovation becomes that much tougher. It may be unethical to run experimental tests on somebody’s heart, for example, and you can’t stop traffic in a city’s rush hour to experiment with new routing systems. Or can you?
SenSat, a company specializing in creating digital twins of cities, believes you can. Its chief scientist, Sheikh Fakhar Khalid, explains, “We created a digital twin of Cambridge, England, and removed all traffic from its streets. This allows the city to experiment with new traffic systems. The model is already being used to plan 5G mast locations. Beyond that, we see many other possibilities: a training platform for autonomous vehicles, cityscapes for interactive content providers, and gaming, and so on.”
Some of the biggest advances are happening in health care, an area where innovation is often limited by ethical concerns. Consider the case of cardiovascular disease. Drawing on anatomical knowledge and thousands of heart images, Philips has created Heart Model, a digital representation of the human heart that can help clinicians diagnose cardiac images up to 80% faster and with fewer variations than traditional methods allow. “With digital twins in health care, you can evaluate different scenarios and treatment options; you can combine personal and medical data to provide real-time intervention and prevention,” explains Ger Janssen, department head of the digital twin department at Philips. “We’re looking not just at cardiology but also oncology, pulmonology, and neurology. A digital twin of the human body is the ultimate goal.”
The impact that digital twins can make is huge. Many are just now in development due to the complexity of their creation, but soon millions of things will have digital twins. And their usefulness and capabilities will continue to evolve.
Collaborating twins: Just as humans collaborate to innovate, so too will digital twins. Much of the value associated with digital twins arises from a digital thread, a connecting infrastructure that allows digital twins to share information with one another and connect traditionally siloed functional perspectives. Consider a car ride: You want to get from point A to B; however, you are siloed from every other driver. If every driver knew where everyone else needed to get to, travel time would become shorter for everyone. Connecting the digital twins of cars enables a fully autonomous car grid and innovation in mobility systems. Siemens does this with robots in its Bad Neustadt factory in Bavaria, Germany. The digital twins of two — or more — of these robots can communicate to figure out how to best work together on a new assembly line.
But it doesn’t stop there. Linking the digital twins of completely different types of assets can feed the digital twin of more complex entities. An entire city, for example, will need to connect information from digital twins tied to traffic, weather patterns, pollution, citizens, energy, and other resources. This enables a transformation from smart cities to conscious cities — cities that are aware of assets flowing in and out of their borders. This level of understanding unlocks new avenues for innovation: new forms of urban mobility that are both faster and cheaper, elimination of congestion; reduction of pollution; new ways of emergency planning; and smart tracking of energy and water. A digital twin with all the complexity and detail of a physical city provides a larger and more valuable platform for experiments than has ever been created.
Corporate innovation: Similar to its promise for cities, digital twins can connect all of an enterprise’s information, providing companies with a real-time holistic view of their operations, and allowing them to swiftly improve operating models, develop better strategies, discover new pockets of efficiency and, perhaps, finally eradicate silo mentality.
Companies will also have a powerful new tool in business model innovation. By adopting digital twins, they can more effectively shift from the production and sale of a product to selling the use and maintenance of that product as a service.
Consider Kaeser Kompressoren, a German company that used to sell air compressors. After introducing digital twins, it has moved toward selling air-as-a-service, where the customer only pays for their use of the compressor.
While some companies have made the transition from product to service without the aid of digital twins (for example Rolls-Royce with its “power by the hour” offering for aircraft engines), the ability to continually improve and innovate complex products changes the value equation for customers and companies alike.
Multiplier effect: The coming of age of digital twins is happening at a time when many other new technologies are finding their footing as well. Digital twins will combine with other emerging technologies to multiply their potential for innovation.
When digital twins are designed with virtual reality capabilities, for example, the immersive views and natural interaction that VR offers makes tweaking designs more instinctive and less cumbersome. Simulations can be run in real time to observe what the product in action will look like, allowing for rapid-pace design phases. Furthermore, your actions in VR with a digital twin could be physically replicated by using robotics. Imagine a surgeon performing a remote surgery using the digital twin of a patient’s heart.
Indeed, the marriage between machine learning and digital twins may even be the answer to the slowing growth of innovative ideas. What if we could let a digital twin create ideas for us? Similar to the infinite monkey theorem, machine learning can be applied to a digital twin to create countless variations of the twin and come up with new patterns, solutions, or creative ideas that humans may not have considered. Recall AlphaGo’s famous victory over world champion Lee Sedol in the ancient game of Go, where AlphaGo made a number of decisive moves that Lee suggests no human Go player would have made.
Inspiration, ingenuity, and tenacity will always be the spur to innovation. Digital twins offer the opportunity to accelerate and multiply these qualities. It’s not too soon to be asking yourself how your company can seize the innovation advantage in this new mirror world.