Science fiction has been promising us all digital versions of ourselves for a long time. We’re still waiting for Ready Player One-style virtual avatars, but digital simulations of real-world objects, devices, and even cities are already here. Today we are going to see an overview of Digital Twins, what they are, and how they’re used. Let’s get into it.
Table of Contents
What is a Digital Twin?
A digital twin is a virtual version of a physical object, process, or place that serves as a real-time digital counterpart. Digital twins are built by gathering all the information about really anything you want to make, and then recreating it in a digital space. Digital Twins help make complex, costly, and even dangerous processes safer, more affordable, and more achievable.
How does it work?
They’re one of the key enabling technologies that are making digital transformation possible. Building digital twins is far from simple, but once created they offer nearly limitless potential. Every individual component, the ways those components interact, and often even the environment they exist in, are replicated. The digital twin then uses artificial intelligence to simulate and demonstrate the effects that change in design, process, time or conditions would have, without having to subject the real-world object to those same changes.
Real-world Examples
1. Aerospace Industry
Want to see what impact a hundred and twenty-degree weather might have on the performance of your jet engine, but don’t want to risk flying one through the desert? Just increase the temperature on the digital twin.
2. Manufacturing
Interested to learn if changing the maintenance schedule on your factory full of laser cutting machines will have a positive or negative impact on production. If you’ve built a digital twin of your facility, simply change the schedule there and find out.
3. Traffic Pattern
Trying to optimize the traffic pattern around a new stadium being built downtown? Adjust traffic light timing, one-way street direction, or intersection design on the digital twin of your city and analyze the results.
Internet of Things
In a digital twin, sensor information from the real world is continuously gathered throughout development, production, and operation, and fed to the digital twin model. With that constant flow of data, changes made in the real world are reflected in the digital twin, allowing it to evolve as the project does. Digital prototypes can be created, tested, and refined during development, well before creating a physical product.
When a product does move to production, digital twins can be used to refine the process based on real-time feedback from equipment and operators. Once a product is in the field, its operation can be optimized by using the digital twin to help inform everything from the best possible operating conditions and maintenance schedules to possible design changes or alternate configurations. So that’s your super high-level overview of digital twins.
The Tale of Two Bridges
Problem
The Norwegian Public Roads Administration is piloting digital twin technology to help in this process. Norway today has a national road system of about 5,800 bridges. You have a prediction of the residual life of the bridge and inspection every five years. But there are a lot of issues that you don’t detect with this inspection, like the behavior or the integrity dynamic of the roads, and these sensors, are able to detect movements and they are able to detect how different loads influenced the bridges. Which is not possible to detect during normal, regular inspections.
Solution
They installed IoT sensors, to monitor the global behavior of the bridge. The sensor data is collected and then, broadcasted directly into the SAP cloud solution. If bridge dynamics, then deviate from the preset thresholds, this is some issues alerts.
When a warning arrives…
On April 7th, such alerts were issued from the Norway Stavo bridge. The NPRA was able to immediately divert traffic from the affected area and begin work on a replacement. They were very lucky that they have well planned this. They had enough time to act on this situation before it went any critical and any lives were lost.
Replacement of bridges isn’t just a Norwegian issue. In Germany over 12% of the country’s bridges are in bad shape. And in the US the number is higher than one-third. The NPRA is hoping that real-time monitoring of critical infrastructure will not only increase safety but also help limit costs. The cost for a maintenance action is, is much higher if you have an emergency. You are not able to plan for it, the suppliers can feel, that you are stressed, and the price doubles.
Conclusion
Everyone knows that it’s most cost-effective to be preventative and to be able to use money upfront before you have an event like this. And we are driving for this, not only within the bridges but for the tunnels for the road system itself. Pre-proactive, predictive, and rely on knowledge and data in the people, in the sensor system, and in the software system.
