Digital Twins is the outcome of the fusion of a set of technologies. These are AR, VR, computer vision, IIoT, and low latency wireless connectivity, like 5G. However, this fusion has created a very powerful technology core–Digital Twins. This technology has the potential to fuel creative waves in a number of major sectors for offering better substitutions to our existing ways of getting the job done. In addition to offering better alternatives, these creative waves also pose the threat of disruption to incumbent products, and also industries. It’s not only necessary to leverage Digital Wins, but also most importantly, to detect and cope with unfolding disruptive effects.
Innovation possibilities of digital twins span diverse areas starting from education to manufacturing. Digital Twins technology is a fusion of virtual reality, augmented reality, and computer vision—and many other component technologies. It produces a digital replica of physical entities, whether living or non-living. It encompasses both potential and actual physical assets. The development of digital twins of processes, people, places, systems, and devices expands innovation possibilities further.
Most importantly, digital twins’ development of real-time transformation of entities offers the promise of taking human-machine interface to a new height. The realization of the scenario where robots or machines perform the operation in the real world upon closely following humans’ acts in the virtual world opens immense innovation possibilities of the digital twin. In fact, the digital twin is emerging as a very powerful technology core to fuel creative waves of destruction.
Historical notes on triggering innovation possibilities of Digital Twins
In fact, the concept of using “twins” originates from NASA’s Apollo program in the 1960s. NASA developed at least two identical space vehicles. It allowed the engineers to mirror the space vehicle’s conditions, during the mission, within the vehicle remaining on Earth, which is called the twin. Hence, it was crucial in the Apollo 13 mission, where engineers on Earth could determine the issue and find a solution with the same assets as the astronauts. This concept eventually gave way to fully digital simulations, giving birth to the idea of digital twins.
This concept consists of three distinct parts: the physical product, the digital/virtual product, and the connections between the two products. The connections between the physical product and the digital/virtual product demand real-time data flows from the physical product to the digital/virtual product. In 1991, David Gelernter envisioned Digital Twins in his book–Mirror Worlds. Michael Grieves of the Florida Institute of Technology first applied the digital twin concept in manufacturing. A digital twin in the workplace is often considered part of robotic process automation (RPA). Some experts consider it as part of the broader and emerging “hyper-automation” category.
Leading firms and research agencies are creating digital twins, digital replicas of products. Notable ones are GE, Tesla, NASA. The idea is to mirror a product in virtual space while keeping the digital replica synchronized with the real one. The advantages of digital twins include the provision of allowing various types of analyses on the digital twin that can provide insight on the real one and lead to corrective as well as precise actions.
Enabling technologies—VR, AR, Sensors, Computer Vision, IoT, and 5G
It begins with the formation of a 3D graphics model of objects. The development of those models with 3D rendering through a set of data points is the beginning. Computer vision techniques should capture those data points from images produced by diverse sensors like cameras, LIDAR, and RADAR. Once those 3D graphics replicas are projected with stereoscopic technology, we get the illusion of virtual reality. To further enhance reality, real-life information, including images, is blended with graphics replicas offering augmented reality. The next challenge is to enable physical machines to relay operations done in the virtual space to the real world. It demands the development of semiautonomous systems. The linking of these smart machines over a low latency internet connection to augmented reality systems opens the innovation possibilities of digital twins.
Human beings will be performing operations on the digital twins in an augmented reality environment, which will be closely replicated in the physical world by semiautonomous IoTs. However, to exploit this possibility, key technologies like AR, VR, and computer vision should progress further. Although 5G offers low latency, the high cost of deployment and health issues are still concerns. To realize the possibility where physical objects can live and interact with other machines and people virtually, the Industrial Internet of things (IIoT) technology is in the formative stage now. Here are some examples of the innovation possibilities of digital twins in major sectors.
Education—innovation possibilities of Digital Twins for investigative and online laboratory work
In education, digital twins are a new tool. Instead of experimenting with the real thing, we can investigate physical objects on its digital representation. In addition to addressing the limitation of physical presence, it also offers the prospect of investigating in certain details, which are not often feasible in experimental physical facilities. Particularly, the study of the functional behavior of dynamic phenomena like blood circulation in the human body or the effect of health or light on the movement of electrons or molecules, digital twins offer new insights in education.
Surgical training and operations on Digital Twins
Researchers are developing digital twin models of human organs. For example, partnering with Ecole Polytechnique, Hewlett Packard deployed its supercomputer to create the brain’s digital models for research purposes. Both Siemens and Philips have their versions of a virtual heart. Apparently, they look like the natural evolution to radiological imaging and diagnosis, with detailed depictions of patients’ organs. However, it’s the beginning of creating a snowball effect in fueling creative waves in offering substitutions to our current approaches of training and performing surgery.
This development also leads to personalized medicine. The digital twin concept enables the design of digital heart models based on patients’ data with the same parameters of the given patient (size, ejection fraction, muscle contraction). It opens the opportunity for testing therapies on the model and looks at the outcome to meet the eventual target—selecting the best therapy for the specific patient.
Manufacturing—real-time reconfiguration production plants and remote human participation
In manufacturing, digital twins offer the opportunity of evaluating production decisions based upon analytics. The ultimate objective is to have a convergence between the physical and digital versions. So that interactions between the physical and digital versions seamlessly take place. It’s being predicted that digital twins are poised to revolutionize discrete manufacturing. It is on the way to reducing operating costs and extending the life of equipment and assets. However, for more than a decade, Automobile companies have been using early versions of digital twins for reconfiguring robot operations.
They accomplish it based on a detailed 3D model of automobiles and robots themselves. Instead of shutting down plants for months to reconfigure robot’s joint movements to perform operations, like welding joints or inserting components specific to a particular model, they perform reconfiguration in digital twins. As a result, they save downtime and also avoid the production of faulty products.
Empowering Robots to handle flexible objects
Robots are facing difficulties in handling flexible objects. Robots need to anticipate how physical objects will change shape once they grab. Hence, this information is vital for them to safely apply pressure in picking and placing flexible objects. In fact, it has been a major challenge for enabling robots to perform desired tasks. However, a research group at the University of California, Berkley, has developed the 3D model of more than 300 physical objects upon considering the physics of shape transformation. Robots are using these models to adapt their fingers to holds those objects safely.
The digital twin is an emerging technology. It’s a fusion of multiple technologies. Progress needs to be made in each of the component technologies. There is no denying that this technology is at a very early stage. Nevertheless, it offers immense innovation possibilities in many strategic areas.
