How Digital Twins Are Shaping the Future of Defense System Design

digital twin is a powerful digital tool that allows an original electronics manufacturer (OEM) or an engineering and manufacturing services provider to create and utilize a digital model of a physical product. Digital twins are gaining traction in a number of applications from Factory 4.0 implementations that enable preventative maintenance to advanced smart homes. In design engineering of complex, high-reliability systems, digital twins show great promise.

By Jan Janick, SVP & CTO, Benchmark 

Digital twin technology allows us to simulate a real-world system to identify design and manufacturing challenges and solutions in a digital environment. As such, this specialized technology offers many benefits, including:

  • Preventing costly failures
  • Speeding time to market
  • Reducing the burden of maintenance


Taking this even further, a digital twin allows for a much deeper level of detail in reviewing and interacting with a digital model. Although the ability to build a digital model has been around for some time, a digital twin allows us to combine systems and gain a better understanding of how these different systems react to one another and work together.

For instance, theoretically we could develop a virtual representation of a helicopter cockpit with all the intended integrated systems (e.g., a radio) and then simulate an environment in which the helicopter flies over a radio jammer to understand how we can work around this challenge. This level of flexibility and capability in working with digital models will greatly enhance design, test, and manufacturing, and will enhance the overall design for excellence (DFX) process. But questions remain:

  • How do we organize all this data to make it as effective as possible?
  • Who owns the data?
  • Who is responsible for developing the modeling for various parts and components, and who will drive standards for the systems that make up the digital twin?

Digital twins become even more complicated when we consider how this specialized technology can be used in the aerospace and defense market where system design complexity is increasing and expectations on required time to reach solutions is decreasing. Nonetheless, the Department of Defense (DoD) and primes are paying attention to the developments around digital twins.


The longer that military aircraft, combat tanks, and warships continue in service, the more difficult it becomes to manufacture or source their required parts. Maintaining a healthy supply chain and ensuring optimal performance can, therefore, become increasingly difficult. Since manufacturers can produce exact parts based on a digital model, the DoD is turning to digital twin technology to reduce lead time on part acquisition.

But even beyond overcoming supply chain and maintenance issues, digital twins offer the DoD several additional benefits “from increasing cybersecurity and perimeter defense to enhancing facility operations and planning future development.”1 As digital twin technology becomes more accessible, the U.S. Air ForceArmyNavyMarines, and Coast Guard will continue to look for opportunities to partner with advanced engineering and manufacturing companies, leveraging digital twins to ensure continued mission success.

But current challenges prevent us from realizing all these advantages today. Walking through these obstacles and posing necessary questions, however, will help us better understand where the future of digital twins will likely end up.


One of the main challenges we deal with is organizing and capturing all the different digital models for components, hardware, software, etc. necessary for product development. Take a Bluetooth module for example. For the concept of digital twins to work effectively, the user needs to have each component (e.g., the drivers, compatible software, antenna/RF components, firmware, etc.). However, if each of these parts originates from different suppliers and service providers, who is responsible for the corresponding digital twin of a physical part, component, or sub-system?

Another challenge is working with more sensitive IP, for example, in military system design and development as mentioned above. Having a fully functioning digital twin creates a serious cybersecurity threat since anyone gaining access to the digital twin could arguably recreate the product in the physical world. This potential threat requires putting limits in place regarding access to various aspects of the digital model, further complicating the idea of data creation, ownership, and access.


Currently, there are a few different ways to address ownership, responsibility of creating a digital twin, and accessibility. We outline some of these below:


The first option is having everyone responsible for the part, sub-system, or component also take responsibility for the creation of their respective digital models and own the data for those parts. Although this creates a greater security risk, it is more efficient in terms of quickly developing the digital twin and sharing responsibility for its creation amongst numerous organizations. This option also makes it easier for those individuals to share their models with other systems in which the part might be required, assuming standards for the models and the “simulation environment” are created and supported.


The second option is to have the OEM (who owns the IP to the product) create, manage, and own all aspects of the digital twin. This option would allow for better security since there would be fewer variables in ownership and the OEM would have more control over digital twin accessibility. The downside is that the system design owner would have a large task to create and maintain the sub-system models and data.


The third option involves the evolution of existing simulation modeling capabilities in which a set of companies develops assets for a digital twin operating environment and sells those assets to companies who need them. These companies could range from:

  • Those already involved in the design and development of hardware
  • Simulation software companies that create a library based on assets created using their software
  • Entirely new companies built for the very purpose of creating and managing digital twins

Although there are various pros and cons to each of these models, it is critical that we keep the conversation moving forward.


No one is entirely sure how this is going to play out, but we anticipate that it will be a combination of these different options based on growing concerns around security and accessibility and the upfront investments required. There are the questions around how Machine Learning (ML) and artificial intelligence (AI) will impact digital twins. Nonetheless, these are pivotal questions to ask now as the rise of digital twins is inevitably going to provide a substantial boost in:

  • Expediting the speed to market
  • Finding alternatives in a constrained supply chain
  • Allowing OEMs and service providers to work through complex challenges faster (and without creating multiple passes of hardware and testing)

Want to learn more about what Benchmark’s SVP, Chief Technology Officer, Jan Janick has to say about the future of digital twins? Contact Benchmark today and we’ll put you in touch!

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