#19: How Can Trends Influence Innovation in Aerospace and Defense?
Get ready to be inspired by Morgan Zimmermann and David Ziegler from Dassault Systèmes as they share groundbreaking solutions to today’s challenges in aerospace and defense. Discover how virtual twin experiences and data science are driving transformation, enabling aerospace companies to tackle these issues head-on, especially in the era of supply chain disruptions.
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Meet our speakers
“In aerospace and defense, the major challenge is solving paradigms. How do we manage opposing trends? We need to develop faster to accommodate the growing complexities of products while keeping costs down. By elevating raw data to actionable knowledge and know-how, we can drive efficiency gains.”
David Ziegler
Read the transcript
Narrator: This is Disruptors Unleashed, where we explore innovative technologies and chat with the trailblazers who are redefining industries as we know them. In our last episode, we discussed how MODSIM transforms high-tech engineers, enhancing their speed, efficiency and performance to the next level.
Today, Morgan Zimmermann, the CEO of NETVIBES, and David Ziegler, Vice President of the Aerospace & Defense Industry, will take you deep into the heart of the aerospace and defense industry. Together, they’ll unveil the secrets behind how top aerospace companies handle conflicting trends, accelerate development and drive down costs through virtual twin experiences. Learn how this data science-powered technology isn’t just solving today’s challenges but reshaping the future of aerospace innovation in ways beyond imagination.
David Ziegler: Sure, you know, in aerospace and defense, the major trends or the major difficulties are about solving paradigms. The first question is, how to manage opposing trends? In defense, for example, you need to develop faster with the growing complexities of products while at the same time keeping the cost of operations in defense down. In commercial aviation, you need to increase your production with respect, of course, to the post-COVID delivery and that big trend of the market pushing back as well as managing still a high level of quality of the product and also spending a lot of effort on product decarbonization.
Morgan Zimmerman: When I'm listening to you, these trends are probably shadowing a very major transformation challenge. It's not anymore about just introducing new technology to manage these conflicting objectives; you probably need to rethink the way the organization is built, the way it works and the way it operates.
David Ziegler: So, one key aspect of solving these key challenges is, simply put, to reveal your virtual twin experience, your patrimony of engineering science, but at the same time, confront it with the real world. Leverage what we call real-world experience. For example, flight operations data, maintenance cost and nonconformances. Sometimes, it's really complex. It's not necessarily about leveraging data and dumping it into a data lake. It's more complex than that. I think it's much more about information management.
Morgan Zimmerman: Makes sense. So, what you're stating is to connect the real world with the virtual world. The vehicle to do that is the virtual twin experience, which actually provides the abstraction, the representation model that allows us to interpret all of that data. But in between, as you previously mentioned, that data is, in many cases, just raw data, nonconformances, sensor data and operation data. So, that data needs to be elevated with ontologies and semantics so that it actually matches the virtual model. And this is what we call data science experience, by the way, at Dassault Systèmes.
David Ziegler: Sure. You know, in aerospace and defense, we are lucky enough to have the major OEMs as our customers and not only do we provide solutions to them, but we enable their transformation. With Boeing, Airbus, Dassault Aviation and Lockheed Martin, we are really at the heart of their transformation. One such example is with Dassault Aviation. For Dassault Aviation, we are essentially leveraging all the flight operations data from the fleet of Rafale for the French Air Force. We are gathering all of that data into a semantic lake. We are organizing that data against the virtual twin of the Rafale and we are making sense and knowledge of all that data. That enables, in turn, Dassault Aviation to reduce the cost of sustainment of the fleet of Rafale for the French Air Force as well as maximize the availability of their product for the end customer.
Morgan Zimmerman: In this period, when I'm listening to your example,
the Rafale is an interesting example because, indeed, we said that raw data needs to be elevated to knowledge and know-how, and in the case of such aircraft, raw data is sensor data. But raw data is also feedback from technicians, pilot reports and history of removals and reinstallation. So, elevating all of that data, thanks to data science ontology on virtual twin experience, as you previously said, is a very interesting way to transform those raw pieces of data into actionable knowledge and know-how, which then enables us to drive the efficiency gain that you just discussed.
David Ziegler: And you know, there are many more use cases than purely looking at the world of sustainment. But thinking about another customer, what we are doing is essentially leveraging real-world evidence from the factory floor taking all the nonconformance data not only from the OEM and its employees but as well as leveraging data coming from the supply chain in order to put all of that into the virtual final assembly line of the aircraft and enabling the OEM to deliver their product at a higher quality. And leveraging, of course, all the associated supply chains.
Morgan Zimmerman: That’s a very interesting use case.
David Ziegler: The supply chain is a major problem. We are having so many disruptions in aerospace with largely vast distributed ecosystems and supply chains that it is a major problem in aerospace. Anything you could do to help?
Morgan Zimmerman: We are delivering industry process experiences in the automotive industry, which is probably highly applicable to your industry. We have worked with companies like Renault to understand the impact of volatility on the supply chain on their business. So, the volatility of the supply chain is the volatility of the cost of raw materials, volatility of the cost of energy and shortage of components. And what we are doing is, we are actually projecting these market trends onto the product to be manufactured and onto the production to be made, to do a few things. One is to understand the financial impact at the product level. So, you can adjust the price of the product or the production level for budgeting purposes and then empower, with all of that knowledge, procurement people so that they know how to drive the negotiation with each and every one of the suppliers. Automobiles are industries that have proven to have developed very strong procurement practices. From what I believe, it is probably a bit stronger than in the aerospace industry. Probably leveraging these out-of-the-box industry process experiences that we have for automotive into aerospace is a shortcut to accelerated value for your customers.
David Ziegler: I think that would be great. Take all the lessons learned from the automotive industry into the procurement segment and let’s have a look at how we can leverage that for aerospace and defense.
Morgan Zimmerman: Great, thank you very much, David.
David Ziegler: Thank you, Morgan.
Narrator: Disruptors Unleashed is produced by Dassault Systèmes. For more episodes, follow us on Apple Podcasts, Spotify, Deezer or your nearest streaming platforms. To learn more about Dassault Systèmes, visit us at 3ds.com.
