Siemens VP gives an insider look into CAD, CAE, AI and much more.
Siemens has sponsored this post.
With 2024 rounding the corner, engineering.com sat down with Dale Tutt, Vice President Industry Strategy at Siemens Digital Industries Software. The topic: what engineers can expect from their CAD, CAE, PLM, AI and digital transformation software in 2025.
Writer’s note: This interview has been edited for length and clarity.
What will be the biggest disruptors in engineering and manufacturing over 2025 and beyond?
The obvious answer is still AI and how it’s transitioning some of the solutions our customers are using. More companies and solutions are starting to adopt it, so I think that is going to be one growth area.
The other one is the industrial metaverse. I think that conversation has shifted a lot. There was a period of hype a couple of years ago, but as we’ve continued to develop it — and having it based on physics — the industrial metaverse now brings together a more comprehensive model to visualize operations. I think a lot of companies are starting to see this as a tremendous benefit.
Speaking of the metaverse, how will augmented, virtual, mixed or extended reality (AR, VR, MR and XR) change engineering work in 2025 and beyond?
This is an area I’m always excited about because it can start to change the way people work. In the past, engineering VR workflows were about design reviews. But I think bringing the ability to create within VR makes it a transformational technology.
Engineers have traditionally worked on 2D screens. They might be able to use some tools for manufacturing simulations and clearance checks, but it was done in this 2D world. Sometimes when designing a part there isn’t the necessary context to know how big or small it is. So, being able to design in context — maybe I’m sitting inside the car designing its parts — I can actually see what it looks like. I can touch things, so to speak. The benefit for business is fewer design changes once the process of building those products begins.
With VR, people can also work on the same model in real-time. It can create a collaborative workspace where everybody interacts with the part together. It is unnecessary for everybody to be in the same room looking at the 3D model because everyone is operating in a live environment within the metaverse with the ability to collaborate on the part and communicate.
With AR, MR and XR, as we move into manufacturing and maintenance environments, we’re starting to see benefits. We have the capability to pull up specs while looking at the part. Technicians don’t have to look away at a paper and come back to the part. There are ergonomics behind that. Instead, the information is presented right there and, in some cases, even projected onto the part.
For another benefit, imagine going through the operations to assemble a product. With XR, it is no longer necessary to work in another system to log a completed task. It’s better, from a business process standpoint, to capture those steps as the person does them. This reduces the number of mistakes that can be made while checking off lists.
In the past, people checked things off manually. What happened is that someone would go through all the steps first, as they didn’t want to keep going back and forth. They would then go back to check everything off. That’s when you start missing things on checklists. XR really reduces these chances for errors, and it makes workflows easier for technicians.
Let’s go back to AI. How will it change the role of an engineer?
We’ve seen a shift in tool sets with generative AI coming into play.
Consider the industry’s need for more systems engineers. Systems engineering, in the past, has been very complex. The people doing it were very specialized. Those people are still needed, but it was a small subset of your engineering team.
Now with AI and large language models (LLMs), we’re able to democratize systems engineering. Workers can enter parameters and then the systems modeling tools can auto generate systems models. This provides more engineers access to these tools. They’re able to modify those systems models and generate software code.
That’s how I see the engineering workforce changing with AI. It doesn’t remove the need for specialists. But it gives more engineers access to those specialties.
That said, what is the future of generative design and its potential for creating more sustainable, optimized products?
We’ve seen generative design over the years for solutions like electrical systems and individual component optimizations. Going forward, generative design will be able to take LLMs, look at the IP of a company, and public domain, and enable engineers to consider more designs of complex systems.
In the past, when examining design concepts there were time limitations: “How many options can I look at while still hitting my deadline?” So, the design space might include tens of options. With generative design, the opportunity is there to look at hundreds of thousands of options.
It’s not going to be, “hit the easy button and an answer’s going to pop out,” but it will provide more options to the engineer who can then make better, faster decisions.
For example, consider applying generative design principles to the supply chain. Options such as, “This part may be cheaper but it’s farther away and has a different carbon footprint” can be considered. There is the option to make those trade-offs in a way that were not available in the past. Not only is cost a consideration, but also cost balanced with sustainability. A more holistic picture based on these different design options comes into focus.
When expanding this analysis with data from products in the field, analytics can be leveraged to optimize performance and predict maintenance and costs. As a result, when making the next design iteration, AI is going to pull in the analytics from those real-world products to produce better designs and digital twins.
I think that’s really where AI is going to help transform businesses. It’s opening up your decision space by utilizing more information.
How is AI expected to change the user interfaces of engineering software?
We’re expecting to see AI help automate the mundane. We see already that AI is helping part classification, or predicting future commands based on user actions.
To predict commands, it is easy to say, “well that’s not a big deal.” But think about the hundreds of operations someone designing CAD goes through every day. If we can save 10 to 15 seconds each time, that starts to add up.
Environmental regulations are tightening worldwide. How will CAD and CAE address the growing need for sustainable design and manufacturing?
For decades, industries have optimized around parameters like energy efficiency. For example, in the past, it’s been done to improve the efficiency of cars and commercial aircraft. There’s been interest to do that from a cost standpoint: “How can we reduce the cost of operations?” It stands to reason that by burning less fuel, by definition, less carbon is being emitted.
Solutions like CAD and CAE have been used to optimize cost, weight, quality and manufacturing processes. A lot of those things also support sustainability initiatives.
I think there’s more emphasis on it now. Like CAD and CAE software can now do carbon rollups — like cost rollups. Functionality has been added to support sustainability initiatives.
Carbon emissions are parameters in a company’s CAD model, in addition to other parameters they have been optimizing. With new regulations coming online, they can use a lot of the solutions they have been using with the added benefit of being able to project sustainability data.
What new skills and knowledge areas should engineers focus on to stay relevant through 2025 and beyond?
Think about the transition in the workforce over the last 10 or so years. We’ve seen a lot of engineers moving from being highly specialized to more generalized. In the past, there would be one mechanical designer working on CAD and another doing simulation and analysis.
Now, the tools are enabling engineers to be more cross functional. They’re doing the mechanical design on the 3D part, but they’re also doing the simulation and wire harness design. We are starting to integrate our solutions so that it’s easier for engineers to work with different tools.
The next phase we’re seeing is this movement toward more software-defined products. We’re seeing this in cars and consumer electronics. Software is defining user experiences more than in the past. When wanting to add a new capability — say auto-braking — it is now possible to add that through software and not by making mechanical changes. It is not necessary to send the car in to replace a board.
That’s driving the demand for engineers to understand software and systems engineering. I think those are the skills engineers should focus on.
How will digital twin adoption grow in 2025?
We continue to see companies recognize that they need the digital twin to fully understand their business and to optimize their operations and products. We talk about the comprehensive digital twin — which connects requirements, CAD models, simulation models and all analysis — and how that helps companies optimize and validate designs. Now it is possible to virtually test models because of physics-based digital twins. Then when moving onto physical tests, the user has more confidence and fewer changes. That helps companies avoid overruns and schedule delays, because changes are hard to make once you start building.
Some industries like aerospace and automotive have been doing this for a long time. But we’re starting to see this in medical devices where they’re making greater use of digital twins. We’re also seeing other industries that have been historically “less digital” starting to make the transition.
I think companies that don’t embrace digitalization may find it harder and harder to stay competitive. I’m not saying they won’t be competitive. But I think the companies that adopt digital transformation are seeing benefits and reducing time-to-market. They’re seeing improved performance and are better able to address sustainability regulations. I think it becomes imperative for companies to be able to understand their processes more thoroughly.
What role will quantum computing play in engineering?
I don’t have a good view on the timeline for quantum computing. But I think, in terms of “how it’s going to impact engineers,” it will be a natural evolution of what we’ve seen over the last 20 years.
As computing capabilities advanced, software solutions like CAD and CAE have taken advantage of this. As a result, it is now possible to have a 3D model with higher fidelity then it was 10 or 15 years ago.
Regardless of where computing capabilities go, we’re going to see engineers model systems with much higher fidelity than they can today. They’ll have more confidence in that model because they’re able to create it without simplifying the system to accommodate for computing power.
Going into validation or verification, it is now possible to do more of that virtually and rely less and less on physical tests. Today, maybe 10% or 20% of testing is done virtually and the rest is done with physical prototypes. There’s a point in the future, and it’s maybe four or five years away, where I think we will see that flip. Then, 80% of testing will be virtual and 20% physical — which essentially becomes a validation of your virtual testing.
What about Siemens? What should engineers expect for 2025?
We continue to expand our capabilities in the comprehensive digital twin. Users can expect their tools will become more comprehensive. They’re also going to continue to see more advancements in the use of AI in our solutions. Next, they are going to start to see VR become more commonplace in our solutions. We have a lot of exciting work that we’ve been talking about with customers and they’re going to see some of those things hit in the next 12 months. Learn more about digital transformation at Siemens.
