FuturePrint Podcast
FuturePrint is dedicated to and passionate about the power of print technology to enable new opportunities and create new value. This pod features deep-dive discussions with the people behind the tech as well as market analysis, trends, marketing and storytelling!
FuturePrint Podcast
#291 - Excelitas: AI, Sustainability, & Smarter Packaging
In this episode of the FuturePrint Podcast, Marcus Timson is joined once again by Rob Karsten, who leads the print business for Excelitas in Europe. Rob has been a long-standing advocate of LED curing in print, and since the acquisition of Phoseon his remit has expanded to cover the full Excelitas portfolio: UV, IR, excimer and LED technologies.
The conversation sets the scene for Rob’s upcoming talk at FuturePrint Industrial Print in Munich, where he will explore how AI and sustainability can work together to transform packaging and industrial print.
Rob explains how the move from traditional mercury UV systems to digital LED curing is not only reducing energy consumption, but also generating richer process data. That data, in turn, is the fuel for AI-driven improvements in yield, scrap reduction and process stability. Sustainability, he argues, is no longer just about energy labels - it is about running smarter, more efficient factories end to end.
He outlines the key domains where AI can make a tangible difference today, from material optimisation and packaging design through to predictive maintenance, smart energy use, logistics and inventory management. Rob also talks about the importance of prioritising: not all AI projects are equal, and businesses need to start where return on investment and environmental benefit are easiest to see and measure.
Crucially, he challenges the assumption that sustainability and profitability always conflict. When you treat sustainability as a question of yield, waste and process efficiency, AI and data become powerful tools for improving both environmental outcomes and the bottom line. At the same time, he cautions that AI itself has an energy footprint, and that the industry will need to think systemically about net impact.
Finally, Rob shares a preview of his AI for Industrial Print session in Munich, which will provide a practical roadmap for ranking AI opportunities in packaging and print, and highlight where the “big wins” really are.
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FuturePrint TECH: Industrial Print: 21-22 January '26, Munich, Germany
Welcome to the Future Print Podcast, celebrating print technology and the people behind it.
SPEAKER_01:Welcome to the Future Print Podcast. I'm happy to have back now a frequent guest actually, uh Rob Karsten, who heads up Excelitas in Europe. Welcome back to the podcast, Rob.
SPEAKER_02:Thank you, Marcus. I mean, you've uh known me quite a long time, and ever since Fosion was acquired by Excelitas, you know, we've continued to champion our bet on LED and in the printing industry. And now my role is uh previously just LED for Fosion, now it's encompassing the whole print industry for all our technologies, including the UV and the infrared and Exymer and all that kind of stuff, and of course the LED. So yeah, it's uh it's a scale-up for me, which is interesting and uh makes the printing industry all that more important for us.
SPEAKER_01:Fantastic. And Accelerotests are obviously participating at FuturePrint Industrial Print in Munich. And we have a special AI for industrial print conference on the 22nd of January, and you're giving a talk at that. I wanted this discussion to follow the themes of your talk. Um, give us a little bit of a an overview of the kind of theme of the talk and and so on.
SPEAKER_02:Yeah, so I'm kind of bridging two worlds here. And um what I what I want to do is look at AI and sustainability and packaging and how we make the take the best of both of these and and move that forward. So I'll look at topics. I mean, obviously that you know we have a little bit of time. You can't be overly exhaustive on and on ever on every topic, but we're gonna look at how AI and sustainability in packaging work for material optimization and design. I want to look at predictive demand and inventory management. We could look at uh we'll also include things on smart manufacturing and energy efficiency. I want to look at supply chain and logistic optimization, uh, recycling and end-of-life management. Uh also you know things like consumer engagement and behavior, a little bit about uh life cycle analysis and reporting, and then take all that and say, well, let's rank uh AI applications and packaging in terms of priorities, where you get the best bang for your buck, look at the summary, and then create a bit of a roadmap and then some key takeaways at the end of that. So um hopefully it's gonna be interesting. Um I suppose any one of those could be a subject in its own. Uh, and maybe that's something I will do in the future is trying to address everyone, each of those individually going forward. But the emphasis is really to look at that. It's not gonna be a sales pitch for our products. I'll do a brief introduction about who we are and what we do, and that's about it. Uh, and then really try to understand how technologies, uh, processes uh and design and all these things can be optimized using AI and sustainability. So that's kind of where I'll be coming from.
SPEAKER_01:Yeah, interesting. And and obviously with sustainability and the fact it's a lot to do with data, isn't it? Sustainability, in terms of either being able to track your performance, but also to be able to prove to various people that um, you know, your claims that are made or um certain features of products are actually contributing on a sustainable level, not just on a clear performance metric. Is that is sustainability increasing in your view in the discussions you're having with customers and so on? Because you're in a quite unique position where your technology serves a lot of different markets, aren't you?
SPEAKER_02:Yeah, I think there's a there uh if we look at the LED side of the business compared to say the some of the more hung energy hungry technologies that are uh that exist, we certainly see that growing on a sustainable growth level moving forward. And and certainly a the overall, there are two effects. Certainly the overall market is growing, but also we see that more of the market is converting from existing technologies to new technologies. So moving from, say, a um a high-energy UV mercury type platform to a low-energy, but just as powerful, LED platform. Uh so we see two growth impacts really. Uh, one of the things that you said earlier, which is super important, is the acquisition and management of data. If you're going to be using AI and sustainability, if you really need to, you really need to track what you're doing and understand all the metrics to get a true picture of what the impact is in your design, in your processes, and and all the other aspects we just spoke about earlier.
SPEAKER_01:Yeah, and I and I guess the AI is a broad term, but you've given really good talks in the past around smart factories and that kind of move towards digitalization for a variety of reasons. A, it's far more possible now, and B, economic pressures are placing that as an imperative among businesses. I guess sustainability links with an entire business strategy, doesn't it? Or production strategy, in that the more efficient we are, the more sustainable we are, or is it not quite as simple as that?
SPEAKER_02:I I think that's that that is true. Um in that the more information you have, the better you can manage processes. Um that's why you know you you talk about us moving towards a more digital environment, and that's why I think it's important to use digital technologies in a digital environment, because there's a lot of information that can be gained from, for instance, like we're gonna use our own example, or our you know, our LED light sources are digital lamps, and they fit perfectly within a digital environment. There's a lot of um control and information about the process, about the output. And if you really want to uh have sustainability, well, sustainability is also about reducing uh defects in production about scrap and waste and things like that. So that so it's not just about energy efficiency, it's about the efficiency of the whole process. So if you have technology that allows you to monitor processes more closely and intervene more quickly, then you can reduce scrap rates, you can reduce um production, you can improve yield, uh, and all those things contribute towards sustainability, right? So the better you yield, the more efficient your process is, the better you're making use of raw materials. Uh so all these things kind of feed into each other, right? None of them are exclusive. Uh they're all mutually supportive and interlinked. And I guess that's I think that's what's really important to get out of all this.
SPEAKER_01:Um and with with AI in that mix, uh uh obviously there's large language models and that we've we all use on a day-to-day basis, but I would imagine with AI within the kind of production environment, but also within the design of your own products, it it needs to be quite tailored, right? It needs to be quite contained. It's almost sort of a fit-for-purpose approach as to a more generalist one. Would that be fair to say?
SPEAKER_02:Well, I think that's the thing about AI, is it can be tailored quite specifically to what you need. I think the issue we're dealing with is that there's large data sets of information in terms of how do you interpret that information and how do you get the best out of it. And that was probably quite difficult in many ways, given the you know, the existing systems we had. You had all this information, how do you analyze it? How do you do that in a fashion whereby you can actually make use of that? And I think that's where AI um helps tremendously because it helps you uh be able to, in real time, analyze a lot more information and draw better conclusions from it. And I think the thing with AI as well, it's not perfect, right? So you have to be careful. I think you need to set parameters, you need to uh judge it in terms of the real real world and not just expect everything it tells you to be 100% correct.
SPEAKER_01:Yeah, it's not a silver bullet necessarily. And I think the key thing you've mentioned there is that data first is so critical, isn't it? Because it the quality you know you achieve quality with put being able to put in the right data at the beginning, I would imagine. Yeah, well, absolutely, yeah. What what do you uh you know, if you were sort of you're covering a number of themes within the talk or sub-themes, if you if you were um perhaps giving somebody a bit of advice around the use of AI and sustainability and and and on a j on a more sort of like starting point, what would you say? I mean, with AI, if you if you're starting to implement a strategy, you want to, you know it can add productivity, you hope it will make you more efficient, you hope it will solve problems or even accelerate innovation. What what should somebody do at the perhaps beginning of that journey?
SPEAKER_02:I think, well, you need to set out for yourself a very clear strategy in terms of what you want to achieve with AI. And I think that's part of what uh I'm gonna discuss is about where the high priorities are, where you're gonna get the highest our ROI and the highest environmental impact, right? So I think those are where you need to control ever nobody's got unlimited amounts of money, so we have to decide where we want to invest what we have. And and one of the things I'll be doing at on ranking of AI applications and packaging is to look at where the high priorities are, where you get the biggest bang for your buck, and then medium and and low priorities. But they're still valuable, right? But they're just longer term, they're they're lower ROI and they're they're harder to quantify. But so that that's that's what I'm gonna be doing. And I think that's um hopefully give some guidance to people saying, like, these are the areas where you can get the quickest, highest return. These are the areas in the medium. This is where you're gonna have to do the long-term investment and the hard work over time. You know, things like life cycle analysis and reporting and consumer engagement and behavior, those things are kind of uh hard to quantify. They and they have a lower ROI. But but there's a lot of things you can do at the very beginning in terms of material optimization and design and things like that, where you can get a really big impact on on sustainability and um and uh you know in in packaging. Yeah.
SPEAKER_01:And thank you. And and and in terms of sustain, I'll be interested in what you think, but often there's a tension between commercial profit and environmental concerns, or at least there seems to be the sense that if we if we are sustainable and try to focus on sustainability and be the best we can, it doesn't always correlate equally into profit. Would AI help bridge that gap is in some respects? Like you say, going for the big gains, making a difference there as opposed to trying to do to do everything. Does AI really help that? Because I know that when we're all under economic pressure, and if there's a choice between a product that's, for instance, a very simple example, uh a product that is more environmentally friendly but costs more, we often go for the lower cost option. Does AI help with that? Or is that still it will always be until the prices are actually the same? Or is actually sustainability about efficiency and profitability as well? I don't know.
SPEAKER_02:Well, I think sustainability is is if if we talk about sustainability in terms of yield and and productivity and and those sort of things, then yes, absolutely, sustainability and AI go hand in hand, right? And I think they they lead to more effective production processes, which lead to lower costs, and ultimately that can translate through to more competitive pricing, if that's the route you want to go down, you know, or or increase profitability. So I I think yes, AI and sustainability can be very good business practices. I think um but they have to be kind of combined with some kind of tangible um benefit that you can if you can't measure something and you can't quantify it, it becomes very difficult to justify it. Now you can justify things for other reasons as part of uh an overall um uh direction of the company towards sustainability about economic things. So companies do do these things. I I you know I know for instance there are companies who are banning certain technologies because they see in the future that they think those are going to be problematic for them, but they're taking the costs up front to do that because they're anticipating that over the longer period that those those these issues will arise. Um other companies maybe live in a much more competitive environment where they don't have that luxury. So they might have much smaller margins and and much uh more difficult investment uh decisions decisions to make. So but I think with if you prioritize, then absolutely definitely you can you can definitely get better, certainly improvements in in all kinds of areas, right? In logistics, in design, and manufacturing and um supply chain and all these sort of things can be impacted by AI. What you have to offset, of course, is the fact that AI in itself is very energy intensive, and and we have that whole cloud structure and everything that needs to be supported, the data centers and all these things that form part of AI. And and uh and that needs to be recognized as well. So, how does that relate to the real world in terms of everything you're doing? But you also have to consider the impact of everything that's being done to support what you're doing. So those are more complicated questions.
SPEAKER_01:Yeah, brilliant. Sounds really interesting. I appreciate your uh kind of overview there. Um so yes, Rob will be speaking at Future Print Industrial Printing Munich 21st, 22nd of January. Um, focus on AI and sustainability. We have a a great program for people actually inside the printing technology sector, but also outside as well. So it's really interesting. Yeah, we've got at least five or six speakers from from different parts. May I add as well, it's a very interesting venue. No, you can.
SPEAKER_02:Yeah, really, really interesting venue. The uh motor world. I mean, that's uh I think that's uh a great choice of venues. We'll be in the coal bunker. I think it's it really looks nice. I'm looking forward to it. I mean, everyone I've spoken to said, wow, that looks like a great place to have uh and it you know, really addressing a gap in our market for people talking more about the industrial side of things, right?
SPEAKER_01:Brilliant. Thank you for that. Adding that on, Rob. So yeah, appreciate you joining us today. And looking forward to your talk in Munich in January.
SPEAKER_02:Not long ago. We'll we'll catch up soon. So you marcus.
SPEAKER_00:Thank you for listening. If you enjoyed this episode, you can subscribe now for more great audio content coming up. And visit futureprint.tech for the latest news, partner interviews, in depth industry research, and to catch up on content from future print events. We'll see you next time on the Future Print Podcast.
