As an outgrowth of increasingly sophisticated Internet of Things technology, digital twins build on connectedness to yield even greater business efficiencies.
What is a Digital Twin?
Exactly what you might think–a digital replica of a real-life device, structure, system or process.
A seemingly simple concept. But building a mind-bending bridge between virtual and physical worlds is no small thing. Imagine being able to experiment remotely on a complex machine or system without actually affecting real output. A digital twin includes all the characteristics, operations, and behavior of the real-world original. Akin to the primary benefit of virtual reality training, the ability to test and change a digital twin, without putting an expensive real-life asset at risk, carries huge promise across a variety of industries.
This potential is why Gartner has deemed Digital Twin technology one of this year’s top trends to watch. Their researchers note that, by 2021, half of all large industrial companies will be using digital twins, and companies using digital twins will realize a 10% increase in effectiveness as a result.
Increasing efficiencies with decreasing costs? Now you’re listening. With dropping IoT tech and sensor costs, digital twin technology is becoming more affordable.
Digital twins are not simply 3D models with metadata added. Of course it’s been possible for some years to make a digital replica that looked like a real-world object, but only recently has it become possible to create a replica that would behave and react like the original. Before, there wasn’t enough information available from IoT sensors to truly create a working “twin.”
The massive information streams emitted from today’s smart machines, systems and processes now make it possible to create real-time working models. Digital twins can be endlessly tested with no harm done — and their value increases with time, because the model refines itself as more data flows in. Early digital twins only replicated individual devices or systems, but the technology continues to evolve–and with pace. Users now depend on replicas of interconnected networks of things to orchestrate entire systems with optimal efficiency.
The earliest digital twin application engineered a designed object, such as a wind turbine, bridge, or airline engine. Obviously suited to this purpose, digital twins represent every physical aspect of an asset. GE itemized these aspects to be encompassed by digital twin tech: “Thermal, mechanical, electrical, chemical, fluid dynamic, material, lifting, economic and statistical.”
One GE aviation customer used a digital twin to evaluate the maintenance of aircraft engine blades. He states, “Digital Twins better predict how a blade will degrade over time, so that we can advise customers on the right time to bring it in for maintenance before a problem occurs.” As the technology matures, and digital twins further embody whole systems, their utility doesn’t just increase, it multiplies.
The proof is in the emerging use cases.
As the technology’s potential is recognized, there are more and more digital replicas of biological systems emerging across multiple medical specialties. Healthcare, in general, continues to be an industry on the rise when it comes to data, connectedness, and emerging tech applications. Oncology is one area showing interesting (and inspiring) applications for digital twin capabilities.
Select lung cancer treatments, for example, take the form of aerosol sprays. Statistics revealed that only 20% of these inhaled drugs typically reached the tumor with other nearby, often healthy tissues, absorbing the other 80%. This displacement frequently causes unwanted side effects.
By creating a digital twin of a patient’s airway system, researchers at Oklahoma State University’s Computational Biofluidics and Biomechanics Laboratory (CBBL) were able to test variations in the aerosol delivery system. They experimented with different particle sizes, flow rates, and structural arrangements within the aerosol mechanism. As a result of this fine-tuning, they were able to deliver over 90% of the medication directly to the cancerous region in patients’ lungs.
The capacity to simulate a building design to evaluate design and structural integrity demonstrates obvious value for construction. Infrastructure Magazine states, “Digital twin technology is transforming the engineering and construction industry in ways that have never been seen before. Having access to a virtual representation of an asset before it is built or for an existing asset is changing the way the industry operates and opening up a world of possibilities.” McKinsey reports that digital twin applications “could reduce decision-making cycles in a construction project from a monthly basis to a daily basis.”
Because digital twins constantly synchronize information from multiple sensors, they represent and create a tangible view for real-time complex system reads. In the energy sector, this means optimal monitoring and maintenance for physical assets and systems.
Royal Dutch Shell, for example, ensures the structural integrity of its new offshore oil rig in the North Sea by using a digital twin. The digital model combines with real-time sensor data from the actual asset, in order to provide Shell with continuous visibility.
In addition, there is a significant opportunity for alternative/green energy businesses to leverage digital twin tech to demonstrate capabilities and savings. They can use simulated structures and systems to measure and compare energy output and savings vs. traditional grid set-ups.
As the world’s physical infrastructure becomes increasingly connected, it also becomes increasingly vulnerable to cyber incidents or acts of cyber warfare. Digital twins can help detect abnormalities within the functioning of a physical asset.
GE determined that their digital twin power plant replicas successfully detected and localized 98% of simulated cyber attacks, helping mitigate 50% of these attacks.
Today’s complex information streams allow replications to go beyond the physical world. DTOs, or Digital Twins of Organizations, push and test this technology, and Gartner specifically highlights DTOs in its trends to watch. While digital twins have been used for processes, growing sophistication of AI now empowers them to replicate entire business operations.
Using a DTO allows experimentation with numerous business processes all at once, and will “drive efficiencies in business processes, as well as create more flexible, dynamic and responsive processes that can potentially react to changing conditions automatically.”
When it comes to potential value, having greater control over assets and processes is difficult to quantify. Imagine, if when you were in school, you had a clone of yourself to do your homework (as well as you would), allowing the real you to focus more on the actual subject matter you were learning in class–it’s a bit like that. The proactive nature of digital twin tech allows companies to audit and improve processes, drive innovation, and predict/head off issues before they happen.