The Full Potential of Digital Transformation in Aerospace Factories – Transcript
In this episode of Talking Aerospace Today, Todd Tuthill and Sunil Chhabra explore where the production digital twin fits into the wider digital transformation of aerospace manufacturing.
Patty Russo: Greetings, and welcome to Talking Aerospace Today from Siemens Digital Industries Software. I’m Patty Russo and I’m responsible for global aerospace and defense marketing here at Siemens. Thank you as always, for joining us. In our last episode, we were joined by Todd Tuthill, Vice President of Aerospace, Defense and Marine for Siemens, and Sunil Chhabra, portfolio development for manufacturing engineering here at Siemens. This discussion today is a continuation in our series on the role that smart manufacturing and adaptive production is playing and/or will play in the future of A&D. This is especially important as we consider the pressure on the industry to increase production volume.
Patty Russo: We’ve already talked with Sunil to explore where the production digital twin fits in this push to accelerate digital transformation maturity in the area of manufacturing. So today we’ll conclude that discussion. Let’s get right back into it with a question for Todd. What’s the linkage between a product digital twin and a smart factory or production digital twin? And, I’m kind of throwing a curveball at you. I think I know the answer. I think I know what you’re going to say, but why is it important? Why do I need the production twin and why is it so critical for the future?
Todd Tuthill: So I’ll go back to the basic definition Sunil made of a digital twin. It’s a digital model of a physical thing. So a product digital twin models my product, whatever it is and it, performance wise and also manufacturing wise just like the manufacture of the product, the production digital twin models the factory. And if you think about the optimum way to design a product, you want to do everything in parallel. Don’t want to, in other words, I don’t want to design the product, build a product, test the product and now take the finished, tested thing to the manufacturing team and say, “Can you figure out how to make this at scale?”
Todd Tuthill: Where you’d like to be is once that subsystem for an aircraft or the aircraft itself is through all of its initial testing and development, and it’s done, then you want to say, “Okay, let’s go. Flip the switch and let’s build this at scale.” And to do that, people designing the factory need some understanding of what they’re building. And they’re not using a real physical asset for the first months or maybe a year or two in the development of the aircraft. They’re using a model and they’re asking all these questions and they’re saying, “Well, how, what kind of hardware do I need, how big of a factory do I need, how many of these are, am I going to build?” Which goes to technical answers and market factor. And a lot of just cost factors too. I’ve got to make money.
Todd Tuthill: And all those things need to get simulated and figured out before I build my factory because I don’t want to build a factory that’s too big. That’s expensive. I don’t want to build a factory that’s too small. I want to be Goldilocks like we kind of said in the last episode. And to do that, I need to understand the financial implications, the technical implications, the market implications, you know, for something as simple as how big does this, you know, this particular machine need to be to build a particular part I’m designing. How big does the factory need to be to meet the production rates I need to make? And you need that model of what you’re building to understand the optimal way to build it.
Todd Tuthill: And at Siemens we put that together, we call it the two twins together, the comprehensive digital twin. You know the product and the production, and that that really completes the whole picture that are that companies need to design it in an optimal way, to build it in an optimal way, but then to feed that back throughout the life of the product and the life of the factory to optimize it and make better decisions. That’s kind of the combination of the two and how they work together.
Patty Russo: If a customer supplier is still document-based I, I’m not picking on suppliers certainly, but we do understand there’s a range of capabilities across the industry depending on where a company fits in the ecosystem. We understand some are still paper based, but does a production digital twin work if suppliers are still paper based?
Todd Tuthill: I think it could. I’m thinking back to a customer. I remember a company I worked with many years ago before I was at Siemens. And we were helping them layout their factory. They had a production digital twin. It was physically cardboard, and they had made physical cardboard models of their factory and laying it out. And I wanted to say, you know, that there’s digital ways to do this too, but that was their production digital twin. It was pieces of cardboard that they were putting in various places to see what would fit. And again, it goes back to, you know that whole maturity scale of where are you and where do you need to go.
Todd Tuthill: That particular customer was still using cardboard for their digital twin and it was still helping them make decisions. Now I think we could all make discussions about how doing that digitally might be more efficient, but they used the technology they had. They learned from it and I think you can, you start there and then you grow from where you’re at and it’s not that you got to go to the end of the scale to see a benefit. The benefit in the maturity comes at the next step. So I think the answer is yes. I think that might not be the most optimal way to do the digital twin, but I’ve seen it done.
Patty Russo: But what I hear you saying is that it would definitely be better if it’s a model-based process coming into the production digital twin environment.
Todd Tuthill: Oh certainly. I think we talked about return, we talked about return on investment. You know, and I think when you talk about better, you’ve got to consider again where you’re at if the whole of what I’m making is a rivet versus the whole of what I’m making is an engine. There are more benefits for the more complex thing I’m building, this complex engine, than a rivet, but there’s different benefits at different scales, and I think it’s not a one-size-fits-all.
Patty Russo: What we’ve been talking about is the potential and the opportunities, so let’s take out the crystal ball like we did in one of our previous episodes, this time with Sunil. What future technologies will make production digital twins even better?
Sunil Chhabra: Yeah, great question, Patty and I, number one I can think about is visualization. Digital twin is all about being able to visualize and interact, create more immersive digital twins. So that’s the number one thing. The number two I think is increasing the AI capabilities. Include large language models to analyze all the data that’s coming in from different sources, be it ERP, be it CRM, be it MES systems. How can we use AI to better analyze that data and provide insights? Think about AI-powered simulations. Can we explore more complex scenarios to optimize our processes? So these are some of the newer technologies I think that can help us make our digital twins even better.
Patty Russo: Is there an instance where the technologies that you just mentioned come into play today? For example, you mentioned immersive. Is that in play currently for production or for manufacturing? This idea of immersive engineering?
Sunil Chhabra: Absolutely. Siemens is collaborating with NVIDIA on their industrial metaverse. How can we create a realistic representation of a manufacturing shop floor? Any changes that are made in the digital environment? Can they be updated in the real world through those connectors? So, so a lot of collaboration is happening within NVIDIA in that space. Siemens is also collaborating with Sony on their product digital twin, where a designer can visualize the product itself in 3D, make changes in a 3D environment, in a virtual environment, and those changes can be written back to the design file. So a lot of immersive technologies that are coming to life between Siemens and Sony and Siemens and NVIDIA.
Patty Russo: Yes. And I would imagine that technology development is going to happen much more quickly than some of the previous generations of technology. So Todd, I’m going to point this next question. To you, the reason I suspect that some of the development of other technologies will happen more quickly is because of the power of AI. And while we don’t want to make this all about AI, I want to ask a question about where AI fits in the continual development, for example, of the smart factory and the approach of the digital twin going forward.
Todd Tuthill: Well, let’s look at a simple scenario, or maybe a complex scenario, a problem that our customers face and we talked about it in previous episodes. It’s the issue of workforce. And you know, we talked about automation changes the level of what human beings do, but it doesn’t eliminate them. It has to elevate them. And part of the issue I think what we have in aerospace is the level of training and the level of proficiency that’s necessary and that creates a barrier. There’s a lot of great people that want to be in aerospace, but they don’t have the training. And things can be complex.
Todd Tuthill: So imagine, if you would, a world in the future and a digital twin where I’ve got a 3D and immersive world like we talked about. I’m wearing gloves on my hands, maybe things on my feet with great haptic feedback, and I can go in and I can do all those processes of installing, maintaining, fixing complex things on an aircraft and I can do things that that might even be safety critical for me, where I could be, I could be hurt. And just like where a pilot gets in a flight simulator and flies all the bad day scenarios and things fail, let’s talk about, you know, I’m doing all those things around the these, this, this aircraft that’s dangerous and I can play all those scenarios. I can learn about that. And think about the safety implications.
Todd Tuthill: Think about the productivity implications of not having to have an apprentice follow around an expert to learn all about it, but they can go in and do all those things and make all those mistakes and gain that learning so much faster. So that’s the immersive part. And then you talked about AI. There’s an enormous amount of information and an enormous amount of data and things that you need to know. So, I can take the 3D environment that I had in training and now I can now go out and make it AR, the AR where I am, superimpose the digital things in front of me, and if I can use a large language model. Have a conversation with, how do I do this? Where do I find that?
Todd Tuthill: What’s the best way to do this? I can start having a real live conversation with natural language with the model that that understands everything about this aircraft and all the problems it can have. And if I can combine AI natural language processing with AR, that just makes the time the things that the technicians that are doing that are assembling these aircraft far, far more efficient.
Patty Russo: So Sunil, the last thread to pull on. Where are some of the opportunities for those technologies to enhance collaboration across the ecosystem? Because we know change is constant and sometimes it takes time to reconcile those changes due to the nature of separate entities of the suppliers working with the manufactures.
Sunil Chhabra: Patty, great question again. I think about managing part design changes or revision changes on the shop floor and how they can potentially impact production. A lot of times changes happen so late in production that customers may have to stop production in order to in order to incorporate that change. Well with virtual reality and collaboration, better collaboration in a virtual environment, manufacturing can analyze the impact of a product design change before releasing it to the shop floor. So this technology working with the suppliers can help, really seamlessly help manufacturers to adopt these changes. So I think that’s a great scenario where collaboration with these new technologies can improve manufacturing.
Patty Russo: This has been a really informative discussion around how A&D companies can increase their ROI relative to the investment of digital transformation and automation technologies. Todd, is there a statement or a sentence or two that you’d like to use to sum up the series that we’ve just conducted on the topic of smart manufacturing?
Todd Tuthill: Sure. I think about our industry and as aerospace transitions, you know for the various reasons we talked about to higher volume, higher variety kind of industry, there’s this more, there’s this pressure on cost. Because like other industries, the margin in the aerospace industry is also going down. So there’s a pressure on costs. There’s a pressure on making decisions fast on delivering products faster, on reducing that cycle time. And I think companies have a real set of decisions to be made. What are they going to do? How are they going to answer the call? How are they going to continue to grow their business and become even more profitable?
Todd Tuthill: And I think these are new problems, and things are changing in aerospace and we’re not going to solve tomorrow’s problems with last year’s technologies. Companies need to modernize. They need to think about digital transformation throughout their business, they need to think about automation. And these things can help customers grow and do better. We talked about Goldilocks, and you want to get it just right. And we talked about lots of ways to get there. I think if you think about the scope of where we’re at with digital twins and automation and digital transformation that can really help you get it right in the digital world before you’ve really got to spend money in the physical world. And that’s really I think what we focused on in this series.
Patty Russo: Absolutely. Sunil, I’m going to give you the opportunity. Thinking back to the beginning of the series and how we set it up by saying our customers are challenged with this push for volume. Is there anything else that you’d like to say to kind of tie a bow on the topic from today around the production digital twin before we wrap up?
Sunil Chhabra: Yeah, Patty, thanks for that opportunity. I like to summarize it by saying our goal at Siemens with our digital twin is to help our manufacturers to stay in the business of manufacturing. Not in the business of troubleshooting or doing nonvalue-added activities. It’s focused on the business of manufacturing. How can I build that at cost, at quality, and fulfill my orders with due dates? So that’s the whole idea about developing the right digital twin to keep our focus in the right place.
Patty Russo: Outstanding. Thank you for that. Thank you, Todd, and thank you, Sunil, for such an interesting discussion today around the idea of smart manufacturing and production digital twins. It sounds like we really need to in the industry rethink how we approach the idea of manufacturing, and from our conversations, we’ve learned there’s some really great opportunities with technologies available today and on the horizon. So many great insights all around. Thanks again, and thank you to our listeners for joining us in this conversation. I’m Patty Russo. And we’ll see you next time on Talking Aerospace Today.
Siemens Digital Industries Software helps organizations of all sizes digitally transform using software, hardware and services from the Siemens Xcelerator business platform. Siemens’ software and the comprehensive digital twin enable companies to optimize their design, engineering and manufacturing processes to turn today’s ideas into the sustainable products of the future. From chips to entire systems, from product to process, across all industries. Siemens Digital Industries Software – Accelerating transformation.
