If it’s still hard for you to grasp the whole concept of a Digital Twin, do not worry – it is quite a complex topic to wrap your head around. Perhaps you have developed a good understanding of what this new technology means, figured out the benefits of its main processes and got a good idea on its potential from our recent posts dedicated to digital twins, but you are still having a hard time visualizing the practicality of it. In order to clear up the potential confusion and show our readers how digital twin platforms will practically be used in real scenarios, we have researched the most practically understandable examples on how digital twin is used in business.
There are 101 ways on how digital twin tech can be used to increase the efficiency of heavy machinery. To give you a distinct example, let’s assume that there is a company responsible for a wind energy farm. The way they are currently operating their wind farm is purely based on weather conditions, however, the problem is, that they are not sure when they should focus on running their wind farm due to the unpredictability of the weather, wind direction, when they should expect a storm and what will be the average amount of energy generated per month.
By using digital twin technology, they are now able to create a fully functioning replica of a wind farm and see which wind angles affect the turbine wings the most. By gathering digital data that represents how much energy the wind farm generated during the past 3 months, they are now able to successfully predict how much energy will be generated in the next 3 years by simulating the event in the future using digital twins. Moreover, by monitoring the wear and tear damage that was caused by windstorms, they are now able to simulate the same amount of damage to 10 wind energy generators and foresee the average lifespan of their wind farm.
Let’s assume that the airforce is having difficulties predicting the average lifespan of a jet engine or forecasting the potential risks of not performing essential plane engine replacement procedures in order to figure out how long pilots can use an aircraft safely before the potential risk gets higher.
By creating a digital twin of an aircraft’s engine, pilots will have the ability to monitor engine health and progress the simulation 10 hours at a time (during a flight) in order to see if the potential risk of the engine experiencing a fatal failure in the near future. The same concept goes for any other parts of an aircraft. The most fascinating aspect of a digital twin based virtual reality is that you can make future predictions by simulating upcoming events without having to experience them. Finally, the answer to how accurate these future simulations will depend on the amount of data that is being gathered – more data means more accurate answers. If you would like to find more examples of how virtual counterpart technology is used in the aerospace industry, meet us at our practical digital twin example expo – find event tickets. In the seminar, we will go through over 100 real-life instances where virtual simulations are applied.
In order to improve the transportation and travel systems in New York City, the government decides to create initiative and build a digital replica of the city itself. By building out an entire city on a digital platform, engineers are now able to develop digital road systems underground and accurately predict how this new transportation system will incorporate itself with normal roads of New York City. Finally, by having data on the average deterioration rate of a road in one of the busiest streets of the city, they are able to make safe predictions on how often the new underground roads will need to be replaced in order to ensure the security of the new road system.
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