As a mechanical engineer, I feel the part of my job is safe from AI for the time being. I don't think quality training data for good mechanical design exists.
3D CAD is only part of good design. To a tinker-er that is 3D printing simple parts, an STL is fine. But most parts that matter require far more design consideration and detail than simply the geometry data that an STL (or other 3D file) provides.
The majority of parts are accompanied with a drawing, and that is where the real design actually is found: Tolerances, GD&T, materials, processing notes...
Even then, most of the calculations and considerations to build the model and drawing are not explicit in the design documents: Nothing about a drawing of a stainless steel part tells you WHY it must be a stainless steel part. I don't think there is a large set of well documented designs out there to act as training data for an AI system to design an assembly beyond basic 3D parts.
The authors identify this gap, but it's a fundamental problem with the wholesale move to AI in mechanical design.
one of the challenges to making a good data set might be around bad designs and why they failed. if we get to a mechanical agent, its going to need to understand that brass was a mistake and redesign a part as steel and change the design for the new contraints
unlike code, that kind of train of experiment i think will be a lot more expensive to make, since you might actually want to create those parts along the way and not just pretend
That said, I am excited for AI assisted CAD tools. Things like creating and applying global variables to an existing part, complex assembly analysis for part reduction or just making a starting base part can be incredibly tedious and are low hanging fruit for improving CAD workflows with AI imo.
Open-sourced dataset: https://huggingface.co/datasets/daveferbear/3d-model-images-...
Blog writeup: https://www.finalrev.com/blog/embedding-one-million-3d-model...
For example if I search “supercolumns” I get regular household furniture.
The generality of the part descriptions made me chuckle.
> A bevel gear with a circular base and a series of angular, tapered teeth extending radially outward. The teeth are uniformly distributed around the circumference, allowing for meshing at an angle with another gear. The gear's face includes a set of holes, varying in size and symmetrically arranged around the central bore, likely for weight reduction or mounting purposes. The central opening likely acts as an axle or shaft attachment point. The design facilitates the transmission of rotational motion between intersecting shafts, typically at a 90-degree angle.
https://m.media-amazon.com/images/I/41hGjsBlrKL._AC_SL1000_....
I tried Google/Claude etc. But none worked. As per Claude, the technical name for that is Pillow Block Bearing/Shaft Coupling Block/Flange Mount Bracket. Funny thing is, your app didn't return any good result when I search with any of those terms.
After reading your blog post, I searched for "block with 2 holes". And lo and behold, it returned ABC-00162357!
Couple of suggestions: 1) Have a permanent link for each model 2) Show related models when a model is clicked 3) and lastly, show models based on an image
edit: Search for "mounting block" returned ABC-00180735 which is exactly what I was looking for. Thank you so much for making this!
My go-to for CAD files is usually https://grabcad.com/library
I searched this for "WAGO" and "XT90", so I guess not the same use case. Some hits for "Raspberry Pi", though.
From the blog post: Our search demo proves that it works quite well. As anticipated, text search works well, returning sensible results for even irregular or poorly formed queries. It’s worth mentioning that this is very different from 3D part libraries like Thingiverse or GrabCAD. Search in those repositories requires users to tag or annotate parts with a description, the text of which is used in search. Our system takes only an unnamed part as input, requiring no additional labelling.
I guess my interest was more piqued by the "CAD" part.
edit: looks like the data is trained from machinery parts. impressive regardless, but i’d add that to the lander
Ok too niche, except that's exactly the use-case as I see it so if that's too niche then what good is it? Whatever call it pre-alpha poc and move on...
Tried "grommet", got all finger rings. Closer but not close enough to be useful. It wasn't a mix of ringular-shaped objects including grommets, and grommets aren't only round either. None of the rings were even slightly grommet shaped, purely tori and belts, some with add-ons and cut-outs.
Perhaps it needs a couple orders of magnitude more input samples before it becomes useful. And by "useful" I do mean even just as a proof of concept, because I don't see any concept proven here.
There are a few though! Try "dog" or "cookie cutter" for example.
not the best tool for the job of making something organically shaped, but maybe they also wanted to run some aerodynamics tests on it?
its not the only one, and other tools are better suited for something like an apple. you can still post-process it to get it right sized for a printer
I.e. it would not be in dataset because the use cases for 3D apples are outside of typical use cases where people resort to CAD software.
