AI and Digital Twins in the Future of Defense

The current D&A market is experiencing an unprecedented surge, primarily driven by heightened geopolitical tensions, notably the ongoing conflict in Ukraine and rising concerns in the Indo-Pacific. This has spurred a significant increase in defense budgets globally, leading to substantial demand for new and modernized equipment.

Demographics in Western nations present challenges for recruitment into industry and armed forces, pushing demand towards advanced robotics and AI to maintain operational effectiveness. Consequently, there’s a strong emphasis on technological innovation. At the same time, production capacities are under pressure to meet this elevated demand, leading to efforts to increase effectiveness in engineering, production and servicing.

The Role of Digital Twins

Digital twins are increasingly becoming a cornerstone in the industry. In industrial practice, it is the virtual representation of all data and information of a physical asset. This comprises, among other electromechanical and functional logical data, metadata and physical status. The digital twin allows for comprehensive monitoring, analysis, simulation, and optimization throughout the entire lifecycle.

They help to accelerate product development and design by virtual prototyping and decision-making, thus significantly reducing the need for costly physical iterations. The market drives us to change the attitude of how we worked in our closed ecosystem in the past. There is now new talent bringing fresh ideas; at the same time, we are extending the production capabilities with new facilities abroad and starting cooperations with other companies or even competitors. Digital twins are a means to train the workforce so that they become much faster operationally, while they enable collaboration between teams, sites, and companies.

During service, digital twins contribute to optimization of operations and maintenance. With complex, high-value assets like aircraft or advanced weapon systems, they open predictive maintenance capabilities, increasing resilience and operational readiness.

Digital Twins and AI

Using digital twins already offers a lot of options, but Artificial Intelligence (AI) is the “brain” that unlocks the full potential of digital twins.

In the context of engineering and production, AI transforms digital twins from mere models into intelligent and actionable tools. While the complexity of our systems is ever increasing, engineering teams still need to understand the system to make the right decisions. Information is spread in different tools, places, and representation forms. AI algorithms are able to process these immense volumes of data that are coming with our systems and make them accessible for analysis. As an example, engineers are now able to query the AI directly to see if a new requirement is fulfilled or which part of the system is affected.

“Artificial intelligence (AI) is the “brain” that unlocks the full potential of digital twins”

Problem solved? Only to a certain extent. Our products need to prove compliance to regulations, standards, and norms, such as safety, an important but cumbersome and time-consuming-task that must be in full human responsibility. Quality insurance cannot be replaced by AI but may be assisted. Government regulations and company policies need to be specific about the extent.

Application to Maintenance, Repair and Overhaul

The intersection of AI and digital twins also has the potential to revolutionize maintenance, repair, and overhaul in the defense sector, addressing critical challenges like demographic change and system availability.

Due to demographic change fewer technicians are available on the market while the workforce is aging. In parallel, new and highly integrated systems are getting into service in the next years. Expert support is therefore a low-hanging fruit here. Logistics and maintenance documentation, such as handbooks, manuals and the like, are predestined for AI-supported user-friendly assistants like we are used to from chatbots. Diagnosis and fault detection can be highly improved in this way. Everybody who had to go through these analog documents in real conditions knows what I am talking about. These assistants may not only be used in service but also for training maintenance crews: Digital twins can be used as virtual environments for system access, allowing technicians to accommodate, even without having access to the physical asset. Training may also be enhanced with fault detection and repair, which brings me to predictive and preventive maintenance. When applied, the potential to increase system availability is huge, by minimizing unplanned downtime and costly emergency repairs. As a constraint, data security and additional equipment, such as sensors, are adding to the complexity and vulnerability of the system.

Outlook

The synergy of digital twins and AI promises to fundamentally transform engineering, production and servicing.

Still, there are some limitations. Notably, cyber security is paramount when our data is getting more and more structured and accessible. Intellectual property needs to be protected not only against theft but also in industrial collaboration with data exchange. Even teams need to find ways to share their knowledge without losing their identity in a system.

AI still has its technical shortcomings and is evolving so fast that today’s systems may be obsolete tomorrow.

Despite these limitations, I am convinced that future systems will be “born digital,” designed from inception with a twin for continuous lifecycle optimization, from rapid prototyping to preventive servicing. The integration of AI and digital twins will deliver unprecedented speed, accuracy, and adaptability, reshaping future product generations.