0:01 Well, let’s start. Good morning, everyone. First of all, I would like to thank Duann for putting this great set up, I’m really excited about this two days, and I’m willing to meet every one of you. I will, I want to exchange a lot of comments, insights, during these two days. Today we will present computational processes for adaptive biomechanics. My name is Jesus Marini Parisi, I’m the founder and computation design engineer at Moon Rabbit Adaptive Lab.

0:28 Well, this is the first time that we are presented a such important meeting, so I will spend a couple of minutes explaining who we are, what we are doing, and why we are doing it. We will talk a little bit about what is our main focus areas, how do we approach project solving, and two study cases in which we will showcase how do we use computational design in problem solving for our clients.

1:00 La, we are an Italian innovational startup, forming in 2023 by a multidisciplinary, multicultural team, and we are specializing in the area of computational design for consumer products. Our main quarter, headquarters, are in M, Italy. Our mission is to unleash the potential of emerging technologies and create a bridge between the new and the traditional development processes. We blend different FS of expertise and an holistic approach to problem solving, so we are trying to, to combine a team with different areas in order to be really experts in computational design, design engineering, material science, and we really are focusing to create the best visual communication possible to express aware work.

1:42 We conduct research in order to gain valuable insights in to inform our strate, strategies and our solutions, so this is a really critical step in our design process. Besides, we create and participate in events because we like to create bful connections, we like to collaborate, we need to get to know people, we like to expand our network, because we believe that collaboration can drive positive outcomes.

2:10 We explore and experiment new trends and technologies, because by a, st, stay the cage of innovation, we can ensure that the, the problems that we are solving, the solution that we are offering, at the best of possible of today’s technologies. And finally, we like to create visuals, we really engage our projects trying to create the best communication possible to ensure a lasting impact and, and, and the best understanding possible.

2:38 We assist companies in crafting their unique of solutions to modernize and integrate new technologies into the da, design process. We have four focus sectors, performance product design, in performance product design we are focusing in creating the correct KPIs of your designs or your processes, so we go from data collection, data analytics, weate, process automatization, we see how can apply our skills, our engineer, our know, and your products with pride, product performance, so everything that is about achieving a target, achieving a specific characteristic, specific material, specific, I don’t know, like I say, KPIs, that’s the, the focus of our, of our design part.

3:37 Computational design process, this help us to, to create, I mean, this is the part that for us is creative problem solving, so we create parametrical solutions, or custom solutions, or generative solutions, that are basic in, in the creativity of our designers, in the creativity of the workflows that we’re creating, also in the creativity of, can we utilize technology, mathematical formulas and so on, in order to create informal design. We are really proud of this part.

4:31 We are focusing in creating a strong knowledge in simulations, either digit, and in implicit simulation, explicit simulations, we, we try to focus and create the best possible material setop, settings, and so on, in order to help companies to create virtual optimization, which prototyping, in order to create the best inze possible.

Finally, we are focusing, all these areas are convering in design for manufacturing, because we know that the, the sector is evolving, so this evolution has, it will be also an evolution in terms of manufacturing, and something that we are, we believe that it will be great and it will increase, is the parity manufacturing.

4:50 Well, after saying all this, why design systems, design is rapidly evolving, so it’s becoming more complex, we need to see it from different approach in order to solve problems of today, so this starts to en in different kind of collaborations, we need to create cross functional teams in order to, to create a more complex solution, right, because complex problems require complex solution, and, in, if we have different, with different perspective, that’s the best way to approach it.

5:29 So computational designs is also good at this, it help us to create this computational thinking, in which it helps to breaking down systems into manageable parts, and then discretizing into algorithms, into to inase efficiency, to cre scalability and adaptability, so we like to solve this kind of problems. That’s why we have, we are bringing today two study cases of two collaboration that we created across, ross, this last two years, three years.

5:59 So the first one is ETH collaboration with Thomas Bachner, that he is a PH, PhD candidate that ETH, Suk, in which the objective was to create a soft robotic hand using invic technology with BCJ control, with BJ, and the objective was actually to, to pro something that was similar to a human hand, in order to, to see that it’s possible with the use of multimaterial 3D printing, also achieve something as functional and complex like, like a human hand.

6:44 So where do we start? We started from the image point, we created the mesh model, and once we have this initial mesh model we needed to start identifying what are the characteristics of the human H, right, so we need to understand what are the, the ligaments, where are the, I mean, what are the bones, who are the bones, vending, if they are like flat, vending, what are the tendons, what are the pul, where are the, everything that it can be used to, to create a functional element.

7:07 So once we identify all of these elements that are actually there, at least we choose five of them, and then we’re trying to create the intricated model with all of them. So we needed also to consider the, the manufacturing part, so we asked him it, and they, they, they told us like, what to do, what to do, how to create the interfaces between the soft and the rigid, how they do the gradient materials, how can, how they need to be blending together and so on.

7:41 And, and remember, this one is a, a human hand model, so the, the scale was small, so we need to create, we need to follow all this functionality in a human scale, or like human hand scale, with this m, with minimum design requirements, and we need to create the best of it.

8:04 So how do we approach the challenge? The first part of this challenge was to create in a, a 3D model, so we started with a traditional approach, we took R know, we start, we place it, our bones, and then we start creating on top of that. What was the problem of doing something like this, that basically once that we finish, let’s say the, the first finger, because we needed to check if it was possible to create something like this complex, we understood that, okay, maybe we need to move a little bit the poly, maybe we need to change a little B, we need to change something, and this change something was affecting something else.

8:40 So at the end we, we create different options, and we saw that, wow, but if we need to change something, something was moving, so it was impossible to follow up all these design changes in, in a fast way, because of course the timeline was tight. So we said, okay, okay, let’s remove everything and let’s start from scratch. Let’s identify what’s the minimum characteristic element that actually can inform our design, so we understood that the capsule was the element that was ruling all of them.

9:10 So once that we identify this one, we create a shape optimization algorithm in order to, to create the best fitting of the poing, because we wanted to minimize the volume, but we, we don’t want any clash between the component on. So at doing this we create, the best way was to create an session, we create the PO, so on. After that we start building on top of this element, because by building on top of the element we know, we knew that we were able to, for example, parameter sides, parameterize the thickness between the sof and the rid, between the PO, between the tend, between the all the ligaments, in this way we have a more complex design based on a single structure.

9:56 So what we did was actually identifying what that single structure, and then we create the model on top of this. So after eight iterations we achieved the, we, we reached the final result, in which we have a model complex enough to create, to you modify that zone, and then you have some adaptability, so it can be adaptable, we need to run some parts, but of course there are some manual process like the draining H, like the sensor parts and so on, but at the end the base model was created in a parametric way using these tools.

10:29 After this I decid, for example, what if design, computational design, was today, so I took this challenge a little bit further, and then I create a simulation with all this multimaterial setups. Where I wanted to do this, because I wanted to highlight that from 22, from 2024, it’s changed a lot in the computational field. Now, for example, we have the measureless simulations by in solutions, in which we can have multim materials with faster interaction, and this help us to create inform designs.

11:12 So we know that maybe something is going to fail, something is not going to be correct, the ligaments are not well designed, and so on, so we, we can improve our designs, we can improve our boundaries, we can improve the, the resistance, and we can use it to create a better informed decisions. This is called looks BCJ printing, actually it’s a BPA, a p&, or like a b map image, in which you have the graving colors from in gray scale, so you can select the different materials and so on. And then this one is the, the, the final result, in which we can actually see the sof roboting hand moving, and after adding on the mechatronic paror that was included by two Mas.

12:00 Okay, we, our second case study is about performance product design, because what would be best in terms of performance like a, as a springs back, of course. So this is a project collaboration with Pum Innovation, with the Pum Nrol team, Caron W, and Coach. So what do we did here, actually, we took the challenge in how can we get a performance produ FW product using computational design, computational workflows, so we need to understand what the computational simulation has, what’s the biomechanical information, what are the materials necessary to create all of these environments, and push it into a product that actually can be informed, and using these new tools.

12:46 In order to do that we need to create a workflow, so this is the workflow that we use, in which we try to create as much as possible of virtual simulations with fin element analysis, in, in order to create as much as possible of verifications, and then create middle steps of, of, of physical validations.

13:05 Okay, we create a lot of tools, this is, this is, was really, really interesting, because I mean you saw, you see this spaghetti monster and so on, but actually it’s not, it’s a combination of a lot of Clos, a lot of P scripts, it’s, it’s a really combinations of several templates, or several elements, that actually we can modulate, we can, we create for specific tools, for example, to create data analysis, to create parametrical, parametric design definitions, for creating definitive element setups, data visualizations, so we use all of these in order to also being able to create templates.

13:52 And once that we identify what’s the minimum requirement, we create templates, we create the, the characteristic element that we can reuse, in order to, to be able to analyze several data. So this several data needs to come from somewhere, so we started creating like a experimental data collection, provided by for innovation team, so we started analyze how car and moves, were, we create a datation, after segmentation we create different visual of this data, in order to understand what was moving, where was mo moving it, and so on.

14:30 So this enable us to create, okay, once that we created this, also we need to understand what the materials that are involved in this, in this environment, what is the Opel, what is the carbon plate, what is the mid food, the power plate and the spikes, also we have the track that is a h elastic material, so we need, we create the characterization of this material, we trying to put everything together inside a virtual environment.

14:53 What do, what else do we need? We need to create engineering digital models in order to be able to simulate in a, in a degree that is also biomechanical relevant, right, so we create engineered digital models of these different platforms. So this is one of the first results that we have after several hundreds of simulation set toops and so on, time that spend readings, learnings and so on. So we have the simulation, this has speed 160 millisecond, large deformations, high lo, so we can identify critical areas, positionings, carbon plate direction, torsion, and so on.

15:36 So this help us to inform our designs, so this also help us to intera between digital and physical products, so we use these simulations to itate and create features, for example the cla in the C and shoe, we use this simulation to identify what’s the correct position, what is the take off angle, so we, we use this data to inform our design, we calculate the stiffness, we calculate the directions and so on.

So at the end we wanted to highlight that by creating virtual prototyping using data driven design workflows, helps also to reduce the physical sampling, which is something good for companies. Of course we need to have really good material character ation, because the quality of your inputs are as good as the quality of your outputs, we need to do more modations to understand how of we are between digital and physical, and what needs to be improved, because actually this is an interative pro process, is a, it’s a process that is always evolving.

16:47 What the result, of course, he won the, the world championship, but of course everything means part of the, the athlete performance, and, but we believe that we help him with that milliseconds extra to achieve his goals. So by giving this extra push, this extra milliseconds, with the clo, with the specific sness and performance setting, we helping to world to, to, we contribute for this winning.

17:20 What are our takeaways of this design tool developments? It’s important that now the design is evolving, it’s becoming more complex, to create tools, tools that are, can be repeatable, that, that has a meaning, that has a specific thinking behind. We realize that, I mean, we knew the vir prototyping is complex, but it’s something that we actually need to push, because viral prototyping is not reality, but it’s closed, it could be closed, we just need to be sure of your the correct methods and correct material characterizations and so on, in order to create really good informed decisions.

17:59 Data visualization is crucial, data visualization is one of the most important aspects of, of your design, because you could have a really good design but you need to show it, you need to be able to express it to, to the big audience. And of course computational design is a continuous learning field, so we are evolving, we are changing technologies, also pushing the way that, that we are ch, that we are using computational design, of how we are implementing, also the new generation of designer is, is pushing, pushing, pushing more for the use of new technology, so we need to be able to adapt to these continuous changes.

18:41 Well, thank you so much for your time and your attention, this is, this was our presentation, this is our, our data, you can find those, our website, you can write me an email directly to design.com, you can find on LinkedIn, I will be happy to connect and talk more about this, and thank you so much for your attention.