Digital Twin technology means creating a “twin” of a physical product, service, person or process in a virtual environment, allowing simulations and research that help predict potential problems and risks, and help optimize performance ahead of releasing the product or service in the real world. Digital Twin concepts have been around since the early 2000s, but it’s only now that the technology has become more cost-efficient and technically capable enough for use by more and more industries and sectors.
Before discussing Digital Twin technology, it might be prudent to explain what the Internet of Things (IoT) is, and how it has helped bring the physical world into virtual environments. The Internet of Things includes all devices in the real world, equipped with computer chips, special software and sensors that can all communicate with each other, sharing data and incorporating Artificial Intelligence and Machine Learning to execute certain tasks autonomously or with minimal human intervention. A good example of real-world IoT is self-driving cars in a handful of cities around the world. These cars are constantly communicating with road signs and traffic lights, as well as other self-driving cars to better plan their route safely, avoid obstacles and react quickly to changing circumstances on the road.
IoT, coupled with cloud-based computing, has made digital twin technologies much more effective and much more quick. Connected, smart devices placed in the physical world and equipped with sensors collect data in real-time and real-world situations. The situations the physical sensors are put through are what the manufacturer predicts their finished product will need to hold up against. The data collected from each test or simulation is then processed by cloud-based systems and analysis is run according to different contextual, historical and of course business-specific data.
The obvious benefit of digital twins is identifying potential risks before mass-production begins, or a service is rolled out to the public. Digital twin simulations might reveal aggravating circumstances that human experts might have missed. Analyzing all the data might also lead to more efficient ways of editing the product or service and make it perform at optimum capacity, safely, more cost-effectively and for longer.
Several products already rely heavily on digital twin research. Important examples include tall buildings, wind and water turbines and aircraft engines. The value digital twins add to these manufactured and engineered marvels ensures that human lives that rely on good design and execution of things like a skyscraper or passenger jet.
Digital Twin technology is spreading quickly to industries beyond manufacturing, to include healthcare, finance and even social programs being developed by public institutions. Research on healthcare products such as prosthetic limbs and joints, benefit greatly from the increasingly versatile abilities of digital twin products to assess how to improve older models and ensure better quality and performance in prototypes currently being developed.
The rise of digital twins holds a lot of promise for businesses, big and small. The ability to minimize risks before a large-scale roll-out of a service or mass-production of a product, will not just benefit the end users’ experience, but also cut down potential losses from mistakes or surprises that a digital twin can easily predict, and the manufacturer/developer can redesign or improve.
For now, most digital twin impact is felt in the industrial world, with consumer-driven design might mean that end-users and customers help crowd-source data and suggestions in real-time that help make products and services more in line with what their customers need and want. From cars to electronics, fashion to catering, digital twin technology that combines cloud computing with real-world data gathering, is changing the products we use every day at increasing speed, often for the better.
It will be interesting to see which industries adopt digital twin technology next, and how industries that don’t manufacture a product will run digital twin simulations on proposed social, educational or even political processes.