Defense Spending Is on the Rise, and Aerospace and Defense Companies Should Take This Opportunity to Invest in Digital Transformation

The international security scene looks set to become increasingly unstable over the next decade, with situations, such as Myanmar’s coup and deepening relationship with Russia, Taliban’s rule in Afghanistan, and simmering tensions over the Nagorno-Karabakh region, culminating to present a bleak international outlook. These conditions are overshadowed by the Russian invasion of Ukraine, and worsening China-Taiwan relations, with China engaging in large-scale military exercises and Taiwan’s dramatic defense spending increase of 13.9% serving to mirror the early posturing of the aforementioned Russia-Ukraine conflict. This instability will drive a palpable change in the attitude toward defense spending, with governments looking to increase spending substantially. Furthermore, the rising specter of high inflation rates, which will erode defense departments’ buying power, especially in the West, will also serve to push increased spending, even if it does only present a nominal increase.

The U.S. Congress is keenly looking to back larger increases in spending, authorizing an 8.02% increase over the previous year’s budget—US$40.3 billion more than the President’s Fiscal Year (FY) 2023 request—taking the total sum from US$773 billion to US$813.3 billion. The Chinese government is following suit, having boosted its spending by a massive 1.45 trillion yuan (US$213 billion), a 7.1% increase over the previous year, and its fastest growth since 2019. Similarly, the U.K. government has presented its goal to increase defense spending to 2.5% of the GDP by the end of the decade, up from its current 2% level. Other nations around the world will likely follow these trends, particularly North Atlantic Treaty Organization (NATO) members.

Increased defense expenditure means greater demand for military assets, whether it is infantry equipment, or F-35 jets. Aerospace and Defense (A&D) manufacturers will see healthy profits from increases in these budgets. These profits present an opportunity for manufacturers, such as Raytheon, BAE Systems, and Thales, to invest in digital transformation technologies, and not just see increased profits as a windfall gain. Forward-thinking A&D manufacturers have already begun investing in digital transformation prior to the stimuli of increased spending. One example is Lockheed Martin Aeronautics, which adopted Siemen’s Xcelerator portfolio in January to “achieve mission-driven digital transformation.” However, the majority of A&D manufacturers still have a long way to go. The World Economic Forum produces a report on “lighthouse” factories that are at the forefront of implementing Industry 4.0 practices in their operations. Currently, there are no A&D manufacturers that have made the cut into the top 100.

Data-driven Industry 4.0 technologies, such as Digital Twins (DTs) and Artificial Intelligence (AI), are important investment priorities now more than ever due to the need to protect margins, providing increases in efficiency in the production process. For example, DTs can allow manufacturers to simulate and test physics-based simulations on digital prototypes to perfect design processes. This can reduce upfront investments in prototyping, also reducing costs and speeding up design/production cycles.

A&D manufacturers must invest in the following digitally-enabled solutions to gain and maintain a competitive advantage.

Digital Twins

There are three key benefits that A&D manufacturers can seek to leverage from DTs:

• Reduce unplanned downtime of production assets through predictive maintenance, improving production line efficiency. In the A&D market, the DT extends out of the four factory walls, also allowing predictive maintenance on the manufactured product. This allows for replacement parts to be proactively manufactured when a part is reaching the end of its life span.
• Support for remote troubleshooting of equipment, allowing skilled workforces to be leveraged more efficiently following asset failure, so they can guide less skilled staff more effectively for repairs.
• Simulate the performance of new designs to improve prototypes during the design phase and increase the first-time quality of these parts.

Overall, DTs allow for significant improvements to Overall Equipment Effectiveness (OEE) by providing visibility into the real-time health of assets and operations. Notable companies providing solutions in this space are Siemens, PTC, and Dassault Systèmes.

Manufacturing Execution Systems

Manufacturing Execution System (MES) software represents the backbone of digital transformation projects, helping to build the digital thread between level 2 and level 4, monitoring the factory floor, and guiding the production process in real time. It is the framework that many other digitalization projects lean on, and if it is not up to scratch, this will affect the effectiveness of other investments.

Although many manufacturers in the A&D market may well already have an MES, technology vendors, such as Siemens and Dassault Systèmes, have been heavily investing in developing and upgrading MES software for factories in the Industry 4.0 age. A&D manufacturers are likely to be due an upgrade. The biggest changes to these MES offerings are that the MES is now offered as part of a holistic ecosystem of products, and regularly updated and maintained. Dassault Systèmes, for example, offers its MES under the banner of its 3DEXPERIENCE portfolio. Similarly, the Siemens Xcelerator portfolio includes its Opcenter MES.

Manufacturers still relying on older legacy systems may find opportunities for significant OEE improvements by leveraging a newer MES that connects with the rest of the factory in a far more efficient manner and is continuously upgraded.

Artificial Intelligence and Machine Learning for A&D Manufacturing

AI and its Machine Learning (ML) subset offer extensive functionality to manufacturers, ranging from defect detection and quality monitoring to generative design. The complexity of A&D manufacturing provides an ideal environment for the use of AI, as the vast amounts of data produced can be leveraged to improve productivity and lower operational costs. For example, the SAP Analytics Cloud, provides AI-powered analytics capabilities to manufacturers. Its Smart Discovery feature allows automated ML models to highlight relationships in datasets and then automatically generate data visualizations on key trends and insights.