How Are Digital Twins Used in the Aerospace Industry?
Digital twins in aerospace are one of the new ways that organizations are using big data to improve processes and drive innovation in the research and development of exciting technologies.
What is a Digital Twin?
A digital twin is a virtual model designed to reflect a physical piece of equipment that has multiple sensors that relay performance data on its functionality, tracking energy output, temperature, performance, efficiency, and more.
This data over time is applied to the virtual model to let businesses run simulations to study performance over time, the impact of small changes, and what can be done to increase performance and efficiency.
Related Blog: How Big Data is Changing the Aerospace Industry
The goal of a digital twin is to have access to data that generates insights into the effectiveness of current practices and provide a place where businesses can try new things without sacrificing productivity.
Digital Twins Vs. Simulations
Though they sound similar and have key things in common like using digital models and replicating a system, a digital twin takes simulating to another level from reproducing an environment virtually. This provides more realistic outcomes using real-time and historical data.
One of the major differences between the two is the detail and scale of the tests they run. A digital twin is able to dive deeper and run a huge number of digital simulations while a common simulation can only test one process. A digital twin is constantly accessing past and present data and using trends to make predictions on the future which means businesses get a more accurate simulation.
Benefits of Digital Twins
- More Effective Development of Equipment: With a digital twin and the data collected by the sensors, aerospace businesses have more effective ways to test changes to processes to increase productivity.
- Improve Efficiency: In addition to the above, a digital twin provides a great testing ground for improvements to overall efficiency of one machine or a fleet.
- Predictive Maintenance and Lifespan: With collected data, businesses can better predict when a part or machine is reaching the end of its lifespan and become more proactive with maintenance and the ordering of parts and replacements.
How Aerospace Companies Can Utilize Digital Twins
Digital twins present numerous opportunities for businesses in the aerospace industry from extending the life of parts and machines to using data to improve the next iteration of them.
Boeing saw a 40% improvement in first-time quality of parts by using digital twins in development
In R&D, aerospace companies can use digital twins to improve the engineering of new parts by being able to simulate their performance in a huge variety of conditions. How will an engine fair in harsh weather? What is performance like after 300+ flights? This knowledge can now be obtained and used to improve parts, predict when maintenance is needed, and extend the lifespan of machinery, vehicles, and more.
In some instances, machines in development will be doing what no machine has done before or will be headed to places where they can’t be tracked, into space for example. With a digital twin, companies have the ability to monitor them digitally and with 147% more accuracy.
The implementation of digital twins in Aerospace is bringing forth many new possibilities by unlocking datasets that were impossible or very hard to get before by removing many of the challenges of tracking performance while a part or machine is in action.
With a digital twin, businesses in aerospace can unlock more potential out of future and current parts by obtaining the necessary data to understand what’s working, what’s not, and what can be done better in the future.
Learn more about how data and technology can help businesses improve their processes and products with more resources available on Impact’s Resource Center, including our new blog posts on the impact of big data and how AI is being used to innovate the aerospace and defense industry.