PLM, AI, and the Road to 2030 at Infineon Technologies
00:10 Hello, and welcome to the Zoom/Tobele Life Farm, host of the PTC 2026 Electronics and High-tech Exchange. Here with me is my guest, Andy Leidner, VP of IT R&D with Infineon Technologies. How we doing, Andy? Hello. Thank you for having me. It's a great pleasure to be here. Maybe you can tell us a little bit more about Infineon before we, we dive into some topics here. A- as you, as you might be aware, Infineon is one of the key semiconductor industries globally. We do have, our key expertise, in automotive
00:40 industries, in, security and power semiconductors, where we are in leading positions, globally. And that has also exposes us to, you know, competition on a global scale. And it also, it's a driver for innovation, where we in IT, and especially I'm talking for IT, we are in the position to support our internal users, colleagues to use, digital technologies fitting to their business needs. Sure. And today, we've heard a lot about digital
01:10 transformation, and so from the IT side, I'd love to hear more about Infineon's digital transformation journey and kind of where you were, where you're going, what the future looks like, and how you guys do things. When looking to the presentations, we saw today or we were allowed, to participate, what I saw is we, we starting at very different, I would say, levels of automation. Sure. So we have seen in the whole, automation in the production and fab, for semiconductor industries, we have seen high automation since many, many, many years. So we see some aspects that are already solved
01:41 and where we, you know, drive for more in the semiconductor industry in the whole production area. What we did, as a whole digitalization initiative, we have been working as a whole company with different domains of the company, from central functions or innovation, R&D, operations. We have been sitting down together with IT, with su- the subject matter experts, from the business sides, and we defined in digital strategy where do we wanna be in 2030. And from the 2030, we are now working within these domains with the respective counterparts
02:13 on methodology, on processes, on IT, on technology. We are working backwards to see, okay, how can and what do we need to do right now? What do we need to speed up? What are the highest value propositions that we need to implement right now to get to 2030 and achieve our targets? And when you think about the different systems and, you know, integrations and tools and some legacy, some new, and some in between, where does PLM fit in the big picture for you guys, and how is that part of your, your digital transformation journey? So a- at, at the moment, we have been working now for, more than five years, on a, on a PLM,
02:46 roadmap, on a PLM roadmap. And a part of this, digital identity 2030, we also identified an innovation area. We call it the Digi-Power R&D. Sure. And in this area, we talk about the federated unified source of engineering. And there a PLM system is one of the core systems that actually links and w- weaves the thread throughout all the IT systems. So we have hundreds, of IT systems that need to be connected. The subject matter expert systems, its engineering systems.
03:18 So the difference in the semiconductor industry clearly is that we are not putting our models into a PLM system, but we have to work with you jointly to understand what aspects of our products actually makes sense and how do we best model the aspects that are relevant in a PLM system and which of the data actually needs to stay in the engineering systems because they are built for that specific purpose. And, and when we think about Infineon, and you're a, a globally distributed company. You have operations around the world.
03:48 What kind of complexity does that add from an IT infrastructure and systems perspective as maybe, you know, an upgrade for a tool here or a new, a new piece of infrastructure for another team, that needs to be able to partner with, another facility or an OSAT or part of another manufacturing group? How do you guys manage some of that complexity as you continue to grow and, and go more digital? It depends a bit on which organizations or which part of the organizations we're, we, we are looking to. By like we are organized, I take the example from, for the, for my area, IT, R&D, and information management. So there we work with our business
04:18 counterparts from the R&D. And, the parts of this riddle of, of how to understand what is happening is that we strategically have our experts, IT experts working on the same locations, also co-located with the business users. And th- that shortcut some of those, you know, information exchange to understand what is happening, what's going on. That's one aspect of being close to the business. Right. The second part is that we, strive for a very strong global platform and standardization approach to have these active conversations
04:51 with our colleagues. What is a differentiating feature that is needed for our product creation process, and which is a platform service that, you know, has a high value if it's just the same throughout the organ And it's a very active conversation- Yeah that we do have, and this the influ- the influential factors there is, of course, we have different ecosystems that we are dealing with. We have, functional safety. We have IoT. We have different speeds and different requirements that come in this ga- in i- into this game.
05:22 And that makes it a very, I would say, attractive and interesting play. A fun problem to solve. Fun problem to solve, but it's also hard nuts to crack. Yes, yes. And then, you know, 2030 and beyond, I guess in your words, right from the, the IT side, what does, you know, optimize, you know, a- approach and solution look like for Infineon going forward in the future? The key element is we, we always need to have these very active joint conversations with the business to decide and work with them what is the best value. And, going forward, w- what we see is, and it is more a reflection what we discussed earlier,
05:57 I see it very much connected to the semiconductor industry. So there is a high standardization on how front-end fabs are actually working in the semiconductor industry, and I see this also as one of the- Design principles for IT systems, that we have a very highly standardized environment, and you have artifacts and you have data that is actually brought to these platforms to get, you know, all things, computed or calculated that you need, but it flows through a platform that is harmonized and standardized throughout the company. Excellent. And that, that, that will give us the
06:28 opportunity to create this digital thread. There will be hundreds of applications, and there will be thousands of agents and whatever is coming on top of that, but the baseline we need to get consistent and, and then stable. Now, I'd be remiss if I didn't ask about AI. So, you know, in your position, how important i- is AI? You know, are you already really leaning into it and going into production, or is it more of a pilot phase today, or internal use cases primarily? You know, what you can share. We have been very proactive in, in enabling all our internal, users and colleagues to experiment and learn.
06:59 We are at the moment still, I would say, in a very broad exploration phase. And we start to have more informed conversations about, you know, how do we scale certain use cases. And in many of these, AI use case scaling, we definitely find out, oh, we need to get the data right. We need to get the platforms right. We need to get the connection right. We need to get the context for an agent, for an AI, get this context in a form that actually works and produces reliable output. Right. So that is one aspects that we're looking at from a production ready versus experimentation.
07:33 I would say we have all of it. We have some of the use cases, and I would clearly say predominantly in the software engineering area, where it is very clear and obvious that these type of use cases are strong, they have a strong value add, and they go along the whole software development life cycle. It's not about coding, it's really going along the, the whole cycle. Those are the, at the moment, the strongest and clearest, and then there is many other, elements that are now getting worked on and, and formalized.
08:05 Well, Andy, thank you so much for your time and for the insight. Sure enough. And PTC, you know, is very grateful for your partnership with Infineon, and we really appreciate your time. Thank you very much. Nice talking to you.