From faster and cheaper drug trials to fully “conscious” cities, digital replicas are changing the face and pace of innovation.
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.
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 drugintended 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.”
Read the full story on MITSloan Management Review