The Future of Auto Manufacturing: AI Driven Design

The Czinger 21C hypercar concept incorporates a revolutionary brake node, a combination of braking system and suspension upright, using Divergent 3D's DAPS system. DAPS utilizes Metal Additive Manufacturing and generative design powered by AI to create highly optimized structures. Generative design explores numerous solutions based on defined parameters, producing innovative designs. It can optimize parts while considering various constraints and objectives.

Generative design methods include Cellular Automata, Genetic Algorithms, Shape Grammar, L-Systems, and Agent-Based Models. Cellular Automata use mathematical models with discrete cells and predefined rules to create emergent patterns. Genetic Algorithms simulate natural selection to evolve solutions in iterative generations. Shape Grammar employs a vocabulary of basic shapes and rules to create diverse designs. L-Systems model growth and complex structures using symbols and iterative rules. Agent-Based Models simulate interactions of autonomous agents, producing emergent patterns and system-level dynamics.

These generative design methods find application in various industries, including architecture, automotive, and aesthetics. They help optimize components, such as connecting rods, lattice patterns, taillights, and suspension systems, improving performance while reducing weight. However, the use of generative design is still developing, with advancements in AI and computational models continually expanding its capabilities.

In the future, AI-driven generative design could revolutionize engineering and design processes, surpassing human capabilities and rapidly producing highly efficient and complex designs. It has the potential to redefine the roles of engineers and designers, leading to more innovative and optimized products in various fields.

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[abjeh]

Nice vid as always. However, this is known as topology optimization and has been around for at least 30 years+. See Bendsøe and Sigmund's book from 2003 that summarises the techniques. It isn't really AI, unless you employ a very broad usage of the term much like conpanies like Autodesk have done to jump on the buzzword bandwagon.

[ToyotaKTM]

This reminds me of my workshop. Every time I get a new hand tool or power tool, I wonder how I ever, did without it. Each new tool, either improves my projects or reduces their fabrication time. AI is going to add many, new and use full tools, to a designers toolbox.

[Rawi]

Dude, the amount of hard work and passion that goes into your work is noticed and HIGHLY appreciated.

[thelaughingman]

We're about to finally have the weird organo-metallic futuristic stuff we always wanted,

[grillonlacigale]

As a designer, working in civil jet engine devellopement, i can tell you this is future. And by future, i mean FAR future. Like a whole generation, may be two. But it's a thing we already look at....

[grantlauzon]

16:22 Nurburgring suspension tuning at home. If you have a simulator with some form of AI driving like Assetto Corsa and an accurate enough aero/weight transfer model you could build the ultimate suspension geometry, spring rate, shock setup, and alignment. Do the tests with varying seat and trunk loads in various weather conditions. Tire wear, grip, and air pressure could also be randomized to test stability in un optimal conditions.

[Brunoscaramuzzi]

This is just the old but gold Topology optimization. AI can just be used to speed up the process, but AI is the hot thing this days, so...

[mhdm]

AI is the new hotness so all companies started chanting "AI! We use AI!" to bump their stock prices and attract investors. Actually, real-world AI-designing use is very limited and done basically only for marketing claim.
In the field, advanced real-world parts are designed with the now-old Topology Optimization (presented at 3:40, wrongly claimed to be a "generative design algorithm") that are then tweaked / re-optimized / re-modeled by humans. The most time/brain-power consuming part is NOT the (initial) design in CAD, so saying AI will revolutionize it is completely missing the mark. The difficult part is determining part constraints and design goals, and setting up reasonably-accurate FEA/FEM simulations that complete in reasonable time. There's a lot of fine balancing between the various goals reuse/ease of manufacture/assembly/repair) including talking to/negotiating with other teams to improve/work around particularly costly constraints. Which means many edits and long simulations.
As for AI.. it's mostly hype. Sure, a "smarter" topology optimization algorithm could in theory result in a 3% lighter part for the same cost but only the humans in charge could rewrite the constraints / re-design to simplify an assembly and remove the part altogether. 100% win, the best part is no part.

[DigitalJedi]

Generative design is awesome when it can be used correctly. If you look at a close-up die shot of modern computer chips, you'll see branching structures in some areas connecting blocks of logic. These are connections and logic made by generative algorithms. The most obvious example I can think of is the cache structure of Zen4C's tiny cores.

[NomenNescio]

I did a little bit of genetic algorithms as well as cellular automata when I studied CS at uni, I can understand why these has not been widely used until know due to large computing requirements associated with their use.

[Zale]

00:00 The Zinger 21C hypercar concept represents a milestone in Divergent 3D's goal to mass-produce vehicles with limited or no direct tooling in a fully digital end-to-end integrated system called the Divergent adaptive production system (dapps).
01:10 Divergent 3D uses AI-driven generative design to rapidly create complex and highly optimized structures for their vehicles.
02:32 Designers still play a critical role in defining design goals, interpreting the generated results, and incorporating their creativity and domain expertise into the final design.
03:41 Generative design allows for the production of optimized part designs more rapidly than traditional design processes.
05:16 Generative design can be implemented using different computational approaches, including cellular automata, genetic algorithms, shape grammar, L-systems, and agent-based models.
09:30 Genetic algorithms are effective for optimizing part designs by evaluating fitness based on weight reduction, structural integrity, and manufacturability.
12:04 Shape grammar is well-suited for aesthetic design exploration and repeated structure designs.
13:12 L-systems are used to model the growth and development of complex structures and can be applied to various design domains.
15:45 Agent-based models simulate the behavior and interactions of autonomous agents within a system, allowing for the generation of unique and creative designs.
17:25 Generative design technology is still in its infancy, with various computational models being explored, including neural network-based models and swarm intelligence-based models.
18:23 AI has the potential to completely revamp how entire industries operate, particularly in the world of design, by bringing about once unimaginable capabilities and redefining the roles of engineers and designers.

[IllIl]

Very cool! Apart from anything else, the aesthetics of those organic looking parts is just delicious.

[bangerlove]

Notice how the parts look like muscular structures

[ciaran]

Am I the only one that noticed the Thumbnail for this video is about the future and it’s a ICE vehicle combustion part 😅. Electric motors are the future.

[PhucYuBich]

No offensive but i slept good to this video. I put it on before bed. Im rewatching it now. You should make an 8hr video about life and all of its aspects.

[stephenbennett]

I can see the work that went into making this stuff look quasi-simple. Really nice. I work as a computational design architect, and it takes long to make visual explainations that convey these techniques in an interesting, non technical way that goes juuust deep enough to get the point across. Generative design solutions take a lot of investment for research on the front end, and so having a clear explaination of what you're trying to accomplish with the fancy new computer algorithms is really powerful. Thanks again! keep it up.

[VirendraBG]

I am an FE analyst for more than 2 decades, I am working with topology etc optimisation in Ansys, Nastran since 2 decades.
This is new algorithm may be more efficient with time.
But both seems to be computationally expesive. Where as GPU processing might help.
Seems interesting.

[stancooper]

I can imagine some of these highly complex, pared down components would be highly unpredictable in their response to fatigue or minor damage compared to their conventional counterparts.

[winniethepoohxi]

Pretty awesome. I love how AI is creating almost alien looking organic optimized solutions to engineering challenges.

Imagine what a computer processor might look like using this process.

[Russell_Huston]

I'm interested to see how "organic" some of these designs will come to look. I'm thinking of how the bones and cavities of the human inner ear look and how you could imagine suspension components having similar shapes.