AI will be necessary to accelerate digital transformations and design new vehicles.
Siemens has sponsored this post.
Written by Todd Tuthill, Vice President for Aerospace and Defense Strategy and Marketing, Siemens Digital Industries Software.
The enormous breakthroughs artificial intelligence (AI) has had in the past couple years are common knowledge at this point. AI itself is nothing new, but recent advances in hardware and GPU technology have enabled the operation of more sophisticated machine learning models that can handle larger amounts of data and make better predictions, pushing AI past the hype threshold into a legitimate tool to do business with.
These advancements cannot be understated as there is a massive demand for AI, opening numerous opportunities across industries.
Aerospace and defense (A&D) is not only an industry that can benefit from AI, but also one that needs it. Despite the immense growth the A&D industry is expected to profit from in the coming years, a growing worldwide workforce shortage threatens to hinder this progress, exacerbated by increased product complexity from the integration of new technologies. If A&D companies wish to stay in business in the future, they will find AI to be a necessary component in accelerating their digital transformation journeys and producing the next generation of aircraft and spacecraft.
Expecting turbulence
There is a lot to look forward to in the realm of aerospace. For instance:
- Companies are researching different forms of sustainable propulsion.
- Engineers are designing the next generation of defense aircraft.
- The United States is poised to return to the Moon and land humans on Mars.
The future of aerospace has never looked more exciting.
Yet these ambitious goals rely on new technologies, and with these new technologies comes increased product complexity. Sustainable propulsion systems for commercial aircraft and enhanced networking capabilities for drones — for example — present new design considerations that must be integrated within the same or shorter design cycles. Additionally, as product complexity increases, so does tool complexity, as new powerful software is developed to design and validate everything from the smallest microchips to wing shapes. All these considerations and tools will take engineers years to learn, and even longer to become experts in.
This comes at an inopportune time as the industry struggles to overcome a worsening workforce shortage that is spanning the globe. The Boston Consulting Group predicts that by 2030, one out of three engineering positions may go unfilled due to a lack of required skillsets. The A&D industry is expected to create all these incredible products and innovations, but it lacks the engineers to bring them to fruition.
Transforming engineering with AI
AI has the potential to counteract the worst effects of the workforce shortage and growing product complexity. At an individual level, it gives engineers new ways to do their work, transforming how they interact with tools and enabling them to gain knowledge and experience faster.
Many industries are already integrating AI copilot systems into their tools, which engineers can utilize, through conversation, to make their jobs easier. By simply asking questions with natural language, engineers can have the copilot automate workflows and clear mundane tasks, as well as quickly access the copilot’s library of specialized knowledge to better understand the software tool. This lessens the need to have an expert on hand to guide newly hired engineers.
Companies can take a step even further by integrating AI directly into design tools. Not only would the AI be able to learn from expert users of the software tool, but it could also use those experts’ workflows to streamline the use of the tool itself. This enables the AI to develop a set of best design practices to help engineers with everything from component placements to wing shape optimization. With AI helping develop better workflows, engineers will be in a better position to navigate product complexity.
All these applications culminate in multiplying the impact of engineers, allowing them to focus on higher-level engineering and critical thinking as AI handles the mundane work. Not only would this reduce the intensity of the workforce shortage, but it would also create a more attractive working environment to draw in new engineers.
Addressing trust
Despite the excitement surrounding AI, some people are still bound to be skeptical of the technology. There are those concerned about AI being unable to effectively do work that has long been done by humans and the results it generates, while others are concerned with AI’s ability to keep proprietary data secure. The latter is especially important in the A&D industry, as many programs are data sensitive or outright classified.
While these concerns are valid, they are not so different from when previous technological innovations changed how work is done. Therefore, they can be addressed. Efforts can be made to reduce the black box obscuring how an AI comes to its conclusions, as well as educate users to better understand how AI functions and where it could be best applied. Regarding proprietary data, instead of drawing on public information from the Internet, like ChatGPT, the AI of an aerospace company can be run locally. This way it only learns and accesses data from the company’s secure and proprietary data lake.
AI in digital transformation
The capabilities described earlier in this article are just the tip of the iceberg. At a higher level, AI can be the key component to help accelerate companies’ digital transformation journeys to levels once thought impossible.
Most companies in A&D have already begun their digital transformations, making inroads in configuring model-based workflows and data archiving, as well as connecting data across engineering domains and increasing traceability. With AI, however, companies can go even further. Automating mundane tasks and streamlining engineers’ workflows with copilots and tool assistants is just the beginning. AI is already being used to generate component designs, write support documents, find optimized solutions and perform many other tasks that we once thought only humans could do. Right now, these capabilities are limited to single engineering domains, but with every leap in AI technology, they grow closer to applying to full multi-domain physics models.
As products increase in complexity and the aerospace workforce gets tighter, AI is positioned to enhance the work of human engineers and enable the A&D industry to overcome its obstacles. By the time 2030 approaches, AI will have dramatically altered the way A&D does engineering, and there will be two types of companies: those who have gone out of business and those who embraced AI.
About the Author
Todd Tuthill is the Vice President for Aerospace and Defense Strategy and Marketing at Siemens Digital Industries Software. Todd’s engineering background is in systems design with functional engineering and program leadership roles and a strong vision for digital transformation. His 30+ aerospace leadership career spans McDonnell Douglas/Boeing, Moog, Raytheon, and Siemens. His experience encompasses all aspects of A&D programs, including design, model-based systems engineering, software engineering, lean product development, supplier/partner management and program management. In his role at Siemens, he is a passionate advocate for the advancement of digital transformation across the A&D industry.
