Siemens has sponsored this post. Written by Todd Tuthill, Vice President of Aerospace and Defense, Siemens Digital Industries Software.
Products grow more complex with every generation, with the demand on designers growing exponentially as they must deliver smarter, more innovative and more sustainable products within the same or even shorter design cycles. As this demand increases, so does the complexity of the tools used to create these products, with the powerful software used to design and validate everything from microchips to airplanes taking years to learn and decades to master.
Artificial intelligence (AI) is one of the key technologies that will not only reshape the way people and software interact, but also reimagine the design process from start to finish, offering a path to making design tools as intuitive as smartphone apps. While this revolution will not happen overnight, neither is it a far-off dream as AI continues to grow at a breathtaking pace. Companies who fail to adapt risk falling behind their competition, who are blazing forward on the path to AI-driven digital transformation maturity.
AI redefines interaction
Since the release of ChatGPT and the renaissance of generative AI that followed, copilot systems have begun to emerge as a powerful application of AI in the industrial and design sectors, which are dominated by complex, specialized software. Industrial copilots, which are already being deployed across various industries, offer the ability to not only easily automate many mundane tasks, but also conversational access to a vast a library of specialized knowledge.
Using natural language to ask questions and interact with software allows new users to learn and use complex software more quickly and with less need for expert guidance. At the same time, experienced users can seamlessly automate workflows and speed up tasks. However, while industrial AI chatbots represent an important first step on the path of bringing AI into professional software, they should not be mistaken for the end goal.
Building a digital expert
While an AI copilot can help with answering questions or simple automations, this does not address the core issue of complexity. A new user will not know what questions to ask or have a workflow to automate, and even for an expert user, navigating a UI with dozens of menus and thousands of commands is a daunting task. By embedding AI directly into design tools, it can not only learn from expert users as they use the software—capturing valuable domain expertise that is often lost due to retirement or transfer—but also use that knowledge to simplify the use of the tool itself.
By understanding expert workflows, an integrated AI system can intelligently put the next tool in the process just one click away, even if a new user might not know what tool they need next. This process can be extended further, allowing the AI to recommend not just tools but design practices as well. An AI system with a deep understanding of best practices and expert workflows could suggest everything from the best spot to place components on a PCB to the optimal way to reinforce a wing. After all, the best way to learn is often to have someone experienced act as a guide, demonstrating and showing best practices and answering questions.
Having an AI support system integrated directly into the design software can flatten the traditionally long learning curve for professional software, elevating novice users to expert level almost overnight. By using AI to take on the burden of interacting with complex design software, it allows users of every skill level to not only contribute but to focus their efforts on creativity and innovation, not learning software. This can not only increase job satisfaction but allow for more complex products to be designed faster and more efficiently.
Generative design brings it together
AI will not just change the way users interact with design software; it will change the design process itself. Generative design is already a pillar of the modern design process, bringing together design tools, simulation and product constraints in a single, cohesive design space exploration process. But what if things could go a step further? AI offers the potential to enable a truly autonomous design process, accepting a natural language input describing a part or product before using a custom AI-driven generative design model, trained on a company’s own proprietary data lakes of expert knowledge and past designs, to perform every step of the design process. This includes everything from initial design concept to validation and refinement before presenting a finished design for human inspection.
To enable this new paradigm, design companies will need custom AI models trained in-house, which has the two-fold benefit of keeping proprietary IP data within the company that owns it as well as training a model that is fluent in a company’s own design language. Keeping valuable design data in-house alleviates one of the major issues of trust when it comes to bringing AI into the design process since no third party would ever need to interact with the data.
At the same time, a custom AI model would better be able to maintain consistency between past and present designs, maintaining a strong brand identity consistent with the years of hard-won knowledge and experience encoded within a company’s past designs. AI-driven generative design represents the next leap forward of the design process, connecting a complete ecosystem of software with powerful AI automation and natural language processing.
In the future, generative AI will serve a critical role as it bridges the gap between words and back-of-the-napkin sketches and functional digital models. Once the initial creation step is complete, traditional generative design processes take over, using custom AI-powered generative design models to further refine and optimize the design based on a wealth of past design data and expertise, to finally present a finished, highly polished design to the end user.
AI unleashes potential
In the increasingly complex and digitally integrated world of modern design and manufacturing, AI is uniquely positioned to connect people and technology in a way that plays to the strengths of both, with AI moving many of the burdens of professional software away from the user. Over the course of the coming months and years, AI will not just be a novelty in industry, but a critical technology that will upend the way products are designed, manufactured and interacted with. Companies that fail to adopt will find themselves unable to keep up in the fast-paced world of competitors that have continued their digital transformation maturity journey – a journey that will lead to an autonomous, intuitive and integrated design process far surpassing anything that exists today.
This article is the fourth in a new five-part series of articles on digital transformation. Read the first article, The comprehensive digital twin is a foundation for digital transformation, the second article, Software and systems engineering and the future of digital transformation, and the third article, Transforming manufacturing through IT/OT convergence, and don’t forget to check back next week as one of my colleagues takes a closer look at the industrial metaverse.