0:00 Thank you, all right, good afternoon. I’m Brigitte De Vet-Veithen, CEO of Materialise, and I’ll share this presentation together with Egwin, who at materializes, the person that takes care of all of our product portfolio, that, you know, is, is dedicated to the pre-print steps, with, for example, our flagship products, Magic Strea, and others. But by way of introduction, so what we’re going to discuss in this talk is, we see today a lot, a lot of applications of additive manufacturing brought to the market, but a lot of companies are actually struggling to scale the applications, partly also because it’s hard to do this cost effectively and efficiently.

0:46 Now what we’ll talk about in this presentations is this pressing need for bringing the cost down, which can be achieved by making the whole additive flow, from design to print, a lot simpler, taking a lot of the complexity out, automation, and we’ve heard, you know, a lot of these themes already throughout the day, but we’ll also talk about the pressing need for the industry to collaborate in different ways together, in order to attack the challenge that we are all facing today. And I hope that by the end of the presentation that you’ve all gotten a feeling for how you can enhance your additive, if you are in the additive field, your additive capabilities, and how we can look at these challenges in a slightly different way.

1:34 Now, if we look at the future of manufacturing, if I can get the slides to work, and see, no, not yet, I’ll just do it like that, should work. So if we look at the future of manufacturing, which we truly believe in, today we are convinced that there shouldn’t be a trade off between volumes and flexibility, or scale and flexibility, which is what we’re seeing today. What we believe in is that there should be a straight path from some of your innovative designs to transformational products, and that goes a lot faster and easier. We do believe that digital manufacturing can actually power, you know, some of the industries like iros space and medical, which are complex and regulated industries, by the unprecedented levels of position and personalization that additive can offer.

2:34 We believe in new levels of, or enhanced levels of, automation, which make the whole thing easier, more flexible, and which brings us these agile supply chains that we all need, and that reduced cost that we need to scale. And we believe in the ability to fine-tune your applications to certain industries, or even individual s, to create completely new to possibilities, which in some sectors and segments we already see, the medical one being one of them, but not in all, a lot, a whole lot of other sectors. So that’s what we believe in, and we can see that future.

3:16 But if we look at the reality today, that’s not what, where we are yet, that’s not what companies feel today, that those are the possibilities, that possibilities that additive gives. We’ve done a recent survey, and that survey, we learned a lot, a couple of things. One is that for companies today, they don’t need to be convinced about the power of addit, or the possibilities of additive, anymore, but what we need in this industry is more guidance as to how to scale effectively, cost efficiently, as well.

3:48 What we see, I learned from that, that survey, is that companies today are struggling with a number of things. One is the perceived complexity, it’s hard to do additive end to end in a good way, and you need skilled labor to do that, and we don’t have a lot of the skills, skilled labor and workforce available, so that’s an issue. We also learned that companies are struggling with their cost, that I talked about, it’s just too expensive for many of the applications, even though there are ways to bring down that cost, and again, we’ll give you some examples as to how to do that. But they also struggle with the integration of additive in a broader ecosystem, because additive is not an island, it needs to integrate in the other, in the whole ecosystem, the manufacturing ecosystem, and it obviously needs to comply with the regulatory requirements in some of the sectors that we talk about, and that’s the hard thing today.

4:43 Now obviously a lot of the companies in, in this room, a lot of the companies in additive can play a role here, certainly software plays a big role here, and of course, as materialized, we believe that with our KM platform that we have ways to add address that challenge, obviously with, you know, an endtoend software, which goam, which is what goam is, our platform, you can find more efficient ways of generating, well, of, of, of driving your process. Obviously with that software you can connect the dots, collect that data that you need to eventually use machine learning or AI programs on it, you can do plenty of stuff. But what I fundamentally believe is that it’s not just one company that can solve that challenge, we need to solve that challenge as an industry and collaborate better and more than what we’ve done so far.

5:37 Just have a look at, you know, what it means for this industry, we have, we are faced with a myriad of interfaces, platforms, operating systems, and our customers are struggling with the fact that they need to connect software, different pieces of software, together, to get to a seamless workflow. They’re struggling with the fact that, you know, to that, that software, in order to collect the data throughout the system, you need to connect a multitude of the devices, printers, post processing equipment, etc, etc. So it’s not just one company that can solve that, and everybody is trying to solve it, but essentially all that time and resource is going into solving, you know, a basic issue, rather than bringing real innovation to the market. So we need to change our approach, and that’s what I call the collaboration catalyst.

6:32 Let me talk about that a little more. So as an industry, in the additive industry, we, a little stuck. So let’s have a look at how other industries have, you know, what they’ve done, you know, when they were a little stuck and didn’t quite see the growth that they wanted to see. I want to look at the automotive industry, and in particular, electrical vehicles, Elen Musk, Tesla, obviously being a leader in that industry. Years ago, when the electrical vehicles came up, Elen had this dream of really transforming the industry, transforming mobility and driving sustainability with that. But he also realized that if he was going to, you know, with the multitud of patterns that he had built, and the company had built, if he was going to block the way for many others to to come in and and and bring other electrical vehicles to the market, that that wasn’t in the best interest, nor Tesla, nor of the, the whole community.

7:32 So what he did is that he decided to make all his IP publicly available and free for everybody to use. Now let’s have a look at the facts, when he decided to do that, you know, there was only less than 1% of the, the vehicles worldwide were electrical vehicles. Look where we are today, electrical vehicles, I think we, it’s hard to think them away. The, so there’s companies like Audi that say that want to become, by 2035, I believe it is, an electrical vehicle only company. BM BMW, sale 15% of their sales today is in electrical vehicles. So the industry has massively grown, and guess what, Tesla is still the number one. So it has benefited them while benefiting the industry, it can be a win-win. And that’s exactly what we want to do, we want to make a win-win out of the fact that we open up, we collaborate, we share, to the benefit of the industry, and every single company can grow in that environment.

8:33 Now, that’s easy to say that. Let’s give you a couple of it examples of what we are doing as, as materialized, and hopefully that’s going to inspire, you know, many of you in the industry, as to how we can collaborate and change the game, in that way building partnerships with other companies, but also opening up our ecosystem and the algorithm base that we’ve built over the last 34 years, years, for others to use, to accelerate the industry and drive growth, and make it easier and faster and cheaper for customers to scale additive and get to that potential that I describe. I’ll hand over to Awin, to lead us through the rest of the story. Ain, the floor is yours.

So, to highlight a little bit the whole partnership and the ecosystem of coam, you see there are a lot of partners that we have. I want to highlight two of them, two is Simons, and and top. Now what I’ve heard from all of you as well is meshing has its challenges. I’ve heard everybody here facing the challenges of the complexity of the designs, and also pushing them through the printability of the machines. So a few years ago we said, okay, we’re going to open up our Magic’s ecosystem as well, and we’re going to add other kernels, or allow other kernels, to to be part of the Magic’s ecosystem. So we started with Simmons, U, we added the parasol kernel into Magics as well.

9:57 Just a question, how many people know Magics, or using Magics? I, you, okay, awesome, that’s good to see. So we added the parasol kernel, so now you can definitely keep working on your B level, so you can push your cut files, your B files, also into the data and build preparation for add of manufacturing. But as Bradley yesterday also showed, from Antop, what we have done now is also added the implicit kernel from Antop, so basically what we do, because making all these crazy designs is awesome, but getting them printed is a totally different thing. So what we have done is basically integrated the endp kernel in Magics natively, so if you have your crazy designs that you want to print, the heat exchanges, for example, I have noticed that heat exchanges are really hot right now, so that’s awesome to see.

10:45 So we can now push them without any conversion to a mesh or whatever, up until the prints. So data prep, build prep, but also slicing and so on, is now done natively on a implicit level, so that means that you have significant speed increases and performance increases. So this was not printable at all, was not sliceable at all with current technology, and what now happens is that you can slice this complex platforms. So this is just a miniature version, the real part is 60 cm by 60 cm by 45, you can print four of them on the SLM 600 machine, and slicing takes only a matter of hours, like three to four hours. So that’s a game change, from uns sliceable to four hours.

11:29 So this is one thing, but this is only the, the, the, on Magic’s level, so the Magics is the user interface. What we now going to do to push us to next level, because we can’t keep adding kernels to our Magic system ecosystem, we are opening up our secret sauce. Magix has also always been perceived as being protective to its algorithms, but as Ban also said, to push really the collaboration in the industry, we have decided that we’re going to open up the Magics SD case, and materialized as decays, available for the full endtoend production flow. So that means all the algorithms that we have, and we really love our algorithms, we have over 800, on triatic, on Magics, on the build processes, and so on, we will open them up via SDK that you can use in your own workflow.

12:14 So I’m going to give you some examples what we have done behind closed doors, because this is not a product yet, so we’re going to push this to the market soon. We have been validating this with M customization workflows, with automation in data and bill prep, as you have seen in Magics itself, itself, but also created a visualization tool, because it’s really important that we still create a full endtoend solution, to make sure that you have all the tools available at your disposal. So how does it work? So at first we started to change the core of our algorithm, so our algorithms are written in C++, C++ is not really scalable to everybody, so we have changed those algorithms, and we push them to a Python algorithm, so that’s one thing.

12:55 We change the user interface, from Magics all the way to a no flow editor, I have seen from all the presentations here today and yesterday that everybody loves a no flow editor, so here we are, it’s also available there. But documentation, and this is also something that we have seen during a presentation today, it was from Meta Fault, from, from Daniel, making your SDKs available is only wanting, documentation is key, making sure that people can use your SDKs, that they all documented, and we have a full library, every algorithm is documented on how to use, how to implement, and so on. So this will be made available really soon.

13:29 And I want to give you an example on really the power of having a full endtoend workflow, on based on Magic as the case. So I was thinking, okay, what kind of application can we use, first I thought was like, okay, heat exchangers, we have to do heat exchangers, it’s really powerful, but I’m lucky that I didn’t choose it, I’m happy that I didn’t choose heat exchangers. I went for iear, so what you see here is basically a flow on iare. So what you can do, and it’s a little bit stuttery apparently, the video, but I can guarantee you it’s smooth. Basically you can go to an a boutique, get a scan of your face, and all the designs of U of the classes are part of an inventory, but not one phas is the same, we can thank God.

14:13 But what you can do here is you can add your designs that you want, and those designs will be automatically adapted to the shape of your face. You will get a recommendation out of this, you can change your styles as well, and then you can start s ping, I want to have those glasses, I want to override it if you want to, but not, not suggested of course, and afterwards you get a full customized glass eye frame based on the shape of your face, and you get a very nice 3D scan of your face out of it. Not as nice as the the rig that we saw yesterday, but it’s, it’s still pretty good.

14:49 When you press buy, you trigger a fully automated, and I heard Ben, there’s no, no 100% automation can always overwrite this, as you see here, you trigger a order, a launch to order, based on the Magic SI DEC case. So what you see here is that you can still do small design change, so you have to take into account that is based on the geometry of your face that you just scanned, so the design of your frame will be automatically adapted to your scan, and there will be made some, some adjustments. So, for example, the pantoscopic angle, to to make sure that your lenses are reflected well, to to your eyes are changed based on the scan data that we have, and you can always overwrite this as well.

15:30 Now afterwards, if it’s based on metal, I, I, you can start doing your build CB. So one thing that we know is with support generation, for example, if you add supports and you have to do minor design changes, the difficulty is that you lose your supports, there’s nothing as annoying as losing your supports after you’re done, and you have to start over. So what you can do also with these algorithms is basically create a support strategy, and then have a full preservation of your supports, based on the data that you get in, so every time that you get an ey frame in, it will be automatically changed and adapted according to the the changes that need to be done.

16:09 Now most frames are being built in, in, in nylon, so that means that you can also nest them, and as we also saw that that nesting is really difficult to do, but especially for those polymer ey frames, the quality is extremely important. So what you can do, and this is really really unique, and this is really powerful, that you will enable for for you as well, is that you can make your changes based on slice level as well. So you can have a full associativity within the workflow, that you can add your blocks, you can create your slices, you can do your hatches, and out of that you can still make changes that are being fed back into the nested build as well. So you can make changes on slice level, on hch level, and it’s going be be fed back into the workflow, so that’s very unique.

16:54 So this is also the main reason why we have created our own no flow editor, because we have to be able to visualize this, to render this as well, but if you’re using Grasshopper or Rhino or whatever kind of automated workflow, you can also integrate these SDKs as well, this really powerful, and this is something that we will enable as well. So but why are we doing this again? The openness, we really want to share iosd cas as well, to really push this to the end, and this is really unique, because at this moment in time you can actually have one workflow from design to really printed part, that is fully ass, fully traceable, fully full associativity as well, in in the workflow, and that you can always have a check within the workflow itself.

So why are we doing this again? Optimizing and reducing costs, manual and repetitive tasks take a lot of work, take a lot of time, with with highly educated people. We want to scale the production with automation, automation really is key for scaling, but we also want to decrease the time to market for am application. So this is really our way to plan and manage and optimize every step in the 3D workflow.

18:04 So yeah, if you’re interested, let me know, we can really, if you’re already a Magic’s user, we, we can already start talking on on leveraging this. If you’re not a magic us and you really want to integrate these SDKs in your workflow, we can definitely explore what is possible there as well. So this is our way on actually sharing and opening up our ecosystem, so all our 800 algorithms will be made available via and SDK, and you can actually have a additive manufacturing block into your own workflow as well. So that’s it for the presentation, thank you so much for the time.