Circular Innovation: ASML's Reuse Program (with Huib Ijkelenstam)

Welcome to the Technology Pioneers Podcast. This is a series of podcasts recorded at the Business Meets Planet event in the Capgemini headquarters in Utrecht. There's a couple of guests and speakers who will get behind the microphone that share their insights or a little bit of the story that they have told today. So stay tuned for this series of Technology Pioneers Podcasts. So I have a new guest behind the microphone from ASML, can you introduce yourself to our audience please? Yes, sure. I'm Haup Eichelstam. I'm head of the reuse program within ASML, with the objective to make sure we maximize reuse and prevent waste as much as possible. Great, great, great topic. You have been speaking on this event, on the Business Meets Planet event today. Yes. Can you tell our listeners a little bit on what have you been talking about in your talk? Yes, I've mentioned the journey of ASML, but also a little bit about the journey of myself throughout the two years I've been working on this topic, was really an engaged audience so I also really liked the questions and basically how they all tuned in. So they had a key message of my personal journey because till now I had my recent job as product development manager where you try to develop new scanner products, new products on top of the scanner. And in my view, before I started in this job, this is the core of what is important for a company and how after being requested to set up the reuse program, how my view on the complexity and the importance of reuse has changed. The people that asked me already knew that, so I thought it was kind of cute that I was wondering if this is important or not, but when I, as soon as I started, I saw the complexity and how easy it is to underestimate it. Yeah, I can imagine. Well reuse in terms of ASML machines, I can imagine that it has a wide range of topics that you have to address so that complexity comes into play from mechanical to electrical to the software running on it, but maybe also the logistics around it, the maintenance part of it, et cetera, et cetera. Are there specific aspects that make it really complex or is it just everything together? Yeah, I need the connection to the business models, the incentives throughout the chain, logistics indeed, configuration management, data that you either have or don't have. Oh yeah, yeah. Acceptance of our customers, collaboration with suppliers, I think generally still from a distance a bit underestimated in the complexity of getting things changed in that ecosystem. I think if you put that all in a mixer, I think the technology part is actually maybe some strengths, maybe a little bit easier than all the other things I just mentioned. Yeah, I can imagine, yeah. And of course within our company in particular, there's a time to market pressure, and reuse is one of the industrialization topics, but I think because we have such a broad scale of products in mature markets and in new technology introduction, we can also pick the market within the company where the momentum for change is also the biggest. And then when we mature there, we try to expand to the other areas. You scale it up to the other areas, okay, okay, interesting. If you talk about reuse, do we talk about the reuse of materials in a machine that can then be reused into a new machine or is it the reuse of materials when fixing stuff, for example? Yeah, so first of all reuse, even though it's a very big complex topic and the total circularity is just one small piece of the puzzle, it's first of all, it's most important that you need as little machine as possible for a product, and then as it stays, it doesn't break down, and it stays relevant for as long as possible, because if it breaks down you need to replace it, if it's not relevant, you need to either upgrade it or move the system in a place where it's still relevant. That's much better for the environment, but if for whatever reason you have to rely on reuse, then we mainly talk about some other streams, but the biggest streams are return from upgrades and return of defect parts and I explained in the story earlier in the morning that we have agreements with our customers that we are allowed to consume return from upgrade parts if the right wear and tear analysis is done and we can guarantee equally or better performance that we are allowed to consume them in new product assembly, and that creates additional demand options, because you can repair or refurbish something if there is no demand, you can effectively generate more waste, because some material you need to get it back into the right conditions. For sure, it's an interesting one, because I was thinking about the fact that reusing, like you said, you need to know the right wear and tear, etc. That makes the fact that you need data very important, and I can imagine that in the semiconductor industry data is also very sensitive, that's the right word. So how do you work with that? For diagnostics, there is already a certain amount of data available and for a regular parts quality. Most of our service contracts allow us to take back the parts that we replace as integral part of a service contract. So first of all, by owning the reverse flow, you can of course get a lot of data from the parts that come out, but also through our diagnostics we collect data, and customers typically are more sensitive about aggregated data that says something about how they use the machine and the product. The process itself. Yeah, but the data you typically need for predictive maintenance or reactive maintenance, the data is much more low level in the system that by itself doesn't provide enough context for it to be relevant in terms of understanding the customer's process. The process of building their chips or whatever it is that they do. So upfront you already think about the data that you need in order to well measure not only the performance of a machine or when you need to do maintenance, but in this case also designing what kind of data you would need for reusability in this case. Yeah, and we are a bit lucky that there is a lot of business value attached to our parts quality. So driving quality up has always been a very important business driver for us, and in order to drive parts quality up you need to understand the failure mode, and the failure mode typically corresponds also with what you need to address in a repair. So yeah, okay so you can not only reuse the parts, but you reuse the data in this case or reuse purposes. Yeah, but the, yeah indeed, so we already got a little bit of a head start by using the same data from our parts quality, and of course the experience we have with repairing a part partly overlaps with part quality programs, but we also learn new things that we didn't know yet, and we can improve the quality of the part with to stay in terms of circularity prevent that the part actually has to be taken out of system. Yeah, and be scrapped or whatever. Yeah, or repaired, because repair already is impact on the footprint, so it's much better if it stays in the system. Of course, of course, yeah I can imagine that indeed. Well that already gives the direct link to where our business meets planet contributes to sustainability goals towards making somehow the planet a little bit better. Like you mentioned, yeah basically trying to get as much products in the system or keep them in the system is contributing directly to that goal. Because to the, well I would say almost spin off between brackets that quality is being guaranteed. Yeah, so preventing it from failure, that's 100% business and planet are well aligned. And if it breaks down, where we align business and planet is that service of a system, especially because we stay in control of the parts and also the cost associated to getting new parts. So that say the cost benefit of repairing also is a cost reduction that also aligns very well with the planet. There's only parts that economically are not viable to repair, that's where business might or might not meet planet and then you really need to know the CO2 and the emissions and everything to make the right trade-off there. But in general we are also quite aggressive in taking more cost, if a repair is equally expensive as buying a new we would probably still pursue repair because of the additional spin-off of the learning loop. Okay, so on one hand there's maybe kind of an idealistic insight in it that you still want to repair it because of what you learned from it and might be able to use that in next phases or in the future even of other products, right? Indeed, there are some intangible values, one is learning, one is especially the mature systems, sometimes they are confronted with end of supply of certain parts and then part that we would say hey this is at a price level and probably even CO2, I'm not sure if we should repair it, but if you cannot get them anymore then a very cheap part can become very expensive because you would have to start a development program to develop an alternative. If you can get the pool of parts, let's say longer, so your last time buy stock or something like that if you can extend on that. But that's somewhat intangible, you can calculate it, but it's a more difficult calculation, so shortage, sustainability and customer expectation, so there's a few intangibles that add up to the cost-benefit itself. So that's a challenging one, is there any other challenging, what is the biggest challenge that you're working with right now in terms of reusability within ASML? So, it's two-fold, one is because we have more reuse mindset, we start to, first thing we do is stop throwing things away, but that will generate a stock in it and then you need to make sure that your repair capability is ramping up to that, but not only your repair capability, but there's also some internal triage activity where it's not proactively already decided and thought through what the reuse path is, but if the value of the part is hitting a certain threshold, you will reactively still do these assessments, but that takes time and then it eventually accumulates, so that's one big challenge to get balance in the triage capacity and the recondition capacity, and I think the other challenge is to further mature the decision landscape of, now we use cost as a proxy for also CO2, so cost made in transport, we translate in a certain way, cost in material, we translate in a different way, but to understand really the full cost of the whole chain, not only the part, but the packaging and the warehousing and the logistics and the time you keep it as sort of capital on stock, that's also a huge challenge, and a lot of fun, luckily, it's a fun job to be in, absolutely, the program is continuing behind us, so thank you very much for some valuable insights and a little bit, a glimpse in the story that you also told on the business meets planet day, so thank you for that and have a nice day, okay, take care.