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Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

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Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#11

Post by doctorpangloss »

lasermatts wrote: post #8
doctorpangloss wrote: post #6

This looks cool. > Steph and I have a history of working... I have so many questions, since you are experienced. Do you think there should be import tariffs on Chinese made EVs? I know your gut is telling you, don't answer this question, but that is like, the biggest and most important story in autos manufacturing, no? It would be like saying, if cars were extremely cheap, so that everyone could have one, the manufac…

I'll answer in reverse order. Making synthetic data from a 3D model is really nothing too special - it's just a tiny subset of what video game engine does. But there's one extra step required for defect detection: you need to think about where the defects occur (and where the non-defect witness marks occur) and simulate those. Like any startup our biggest advantage here over the big companies is we move fast and cust…

> We'll need a lot of automation and design work to push down US-made EV cost to be competitive.

What kind of automation and design work would "push down US-made EV costs" more than corresponding automation and design work in China?

Do you see what I mean? Technology doesn't change the relative costs, which matter, even if it changes the absolute costs, which don't.

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#12

Post by knicholes »

I apologize for such a naive comment, as I don't have experience in this field, but I've seen OpenAI do some pretty impressive image recognition tasks (multimodal LLMs). Have you tried uploading some images of successful injection castings and some of unsuccessful injection castings (they don't even have to be of the same mold), telling it "These are examples of success" "these are examples of failures, e.g. flashing, blemish, scratch, etc" and feeding it picture(s) of the casted object?

It'd be interesting to hear how effective that is.

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#13

Post by michaelmior »

doctorpangloss wrote: post #11
lasermatts wrote: post #8

Earlier quoted context omitted.

I'll answer in reverse order. Making synthetic data from a 3D model is really nothing too special - it's just a tiny subset of what video game engine does. But there's one extra step required for defect detection: you need to think about where the defects occur (and where the non-defect witness marks occur) and simulate those. Like any startup our biggest advantage here over the big companies is we move fast and cust…

> We'll need a lot of automation and design work to push down US-made EV cost to be competitive. What kind of automation and design work would "push down US-made EV costs" more than corresponding automation and design work in China? Do you see what I mean? Technology doesn't change the relative costs, which matter, even if it changes the absolute costs, which don't.

> Do you see what I mean? Technology doesn't change the relative costs, which matter, even if it changes the absolute costs, which don't.

I get what you're saying, and I somewhat agree. But I think it does leave out the desire some consumers have to purchase domestic. For example, I might be willing to buy a domestically made vehicle if the price is under $25K even if it's more than a similar vehicle made overseas. But if the price is over that, I'm going with the cheaper import.

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#14

Post by lasermatts »

knicholes wrote: post #12

I apologize for such a naive comment, as I don't have experience in this field, but I've seen OpenAI do some pretty impressive image recognition tasks (multimodal LLMs). Have you tried uploading some images of successful injection castings and some of unsuccessful injection castings (they don't even have to be of the same mold), telling it "These are examples of success" "these are examples of failures, e.g. flashing…

LLMs like GPT-4o have some pretty impressive image performance. It can actually pick up some of the more obvious defects on our buckets (Steph tested it out just now).

Two problems though with the OpenAI approach: 1. You'd need a cloud connection to send those images up to and get the answer back down so that's cost in terms of your round-trip latency, network infra, and the OpenAI account itself.

2. It doesn't do well with the very subtle defects - mild shape changes, loss of features from short shots, etc

It might be worth using in the offline pipeline for auto labeling though!

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#15

Post by acyou »

lasermatts wrote: post #10
acyou wrote: post #9

Nice! I have so many questions.. How stable is the injection molding process once it's fully proven out, up and running? Is it a bathtub curve shape, do defects keep randomly popping up? What do you use on your end to label the ejector pin locations, parting lines, etc? Does this process use Hexagon software inputs to make that easier? If you're not relying so much on a skilled operator, would you be using a CMM for…

> Nice! I have so many questions.. How stable is the injection molding process once it's fully proven out, up and running? Is it a bathtub curve shape, do defects keep randomly popping up? They tend to pop up randomly -- mold wear is a big one -- and that's a function of material selected for the mold itself (resin vs aluminum vs steel.) > What do you use on your end to label the ejector pin locations, parting lines,…

Thank you.

I have seen machines with visual pressure curve output on the operator screen for each part. I also think some machines have automatic pressure monitoring already built into the machine control, but it's certainly not transformer model based.

I didn't know they were using resin molds, that takes cheap aluminum prototype scale up mold to a whole new level.

Last time I checked, the mold design software itself has the same UI as 1999 AutoCAD.

How many images/angles can you effectively sample and compare on that hardware in a 30 second cycle time? How would you process images from more than one camera? If you have 8 cameras, can the defect recognition software run on 8 threads?

Are injection mold operators mostly located in low labor cost areas? Is any reshoring happening?

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#16

Post by Slowki »

acyou wrote: post #15
lasermatts wrote: post #10

Earlier quoted context omitted.

> Nice! I have so many questions.. How stable is the injection molding process once it's fully proven out, up and running? Is it a bathtub curve shape, do defects keep randomly popping up? They tend to pop up randomly -- mold wear is a big one -- and that's a function of material selected for the mold itself (resin vs aluminum vs steel.) > What do you use on your end to label the ejector pin locations, parting lines,…

Thank you. I have seen machines with visual pressure curve output on the operator screen for each part. I also think some machines have automatic pressure monitoring already built into the machine control, but it's certainly not transformer model based. I didn't know they were using resin molds, that takes cheap aluminum prototype scale up mold to a whole new level. Last time I checked, the mold design software itsel…

Steph here - each image takes about ~250ms on a small single board compute like an Nvidia Orin Nano. On something larger like an RTX 4080 GPU it's less than 100ms. Because we're running big models we can't really just spin out more threads ourselves, we throw them over to the GPU (or deep learning accelerator - depending on the platform) and the driver's internal scheduler decides how to get it done.

In a robotic packaging scenario most of the time is spent by the robot picking up the objects and moving them, so for a 30 second cycle we usually get less than a second to take multiple pictures and make a decision about the part. For a smaller number of images - like 4 - it's pretty easy to handle with cheap hardware like an Orin Nano or Orin NX. If we've got more images (like 8) and a tight time budget (like less than 2 seconds) we'd usually just bump up the hardware, like going to a higher tier of Nvidia's line of Orins or using compute with an RTX 4080 GPU or equivalent in it.

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#17

Post by lasermatts »

acyou wrote: post #15
lasermatts wrote: post #10

Earlier quoted context omitted.

> Nice! I have so many questions.. How stable is the injection molding process once it's fully proven out, up and running? Is it a bathtub curve shape, do defects keep randomly popping up? They tend to pop up randomly -- mold wear is a big one -- and that's a function of material selected for the mold itself (resin vs aluminum vs steel.) > What do you use on your end to label the ejector pin locations, parting lines,…

Thank you. I have seen machines with visual pressure curve output on the operator screen for each part. I also think some machines have automatic pressure monitoring already built into the machine control, but it's certainly not transformer model based. I didn't know they were using resin molds, that takes cheap aluminum prototype scale up mold to a whole new level. Last time I checked, the mold design software itsel…

Injection molding houses are heavily concentrated in LCOL areas -- but it's a massive market, so, so much of modern materials are plastic that there's a lot that's done in the US/Canada/Mexico, in North America, and Germany/Italy/Austria.

For just the automotive industry, there are 120 injection molding contractors in Michigan alone. Onshoring and reshoring are desired for really customer facing parts -- you spend a lot of weight on packaging to mitigate scratches when you produce abroad then assemble domestically.

Staying with automotive, electrification is driving the injection molding industry -- as your weight shifts to "big battery with a shell around it" more of the total components of a vehicle are injected.

Zooming out of automotive, biomedical device packaging is a huge injection molded business that's stayed in the US and is growing.

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#18

Post by doctorpangloss »

michaelmior wrote: post #13
doctorpangloss wrote: post #11

Earlier quoted context omitted.

> We'll need a lot of automation and design work to push down US-made EV cost to be competitive. What kind of automation and design work would "push down US-made EV costs" more than corresponding automation and design work in China? Do you see what I mean? Technology doesn't change the relative costs, which matter, even if it changes the absolute costs, which don't.

> Do you see what I mean? Technology doesn't change the relative costs, which matter, even if it changes the absolute costs, which don't. I get what you're saying, and I somewhat agree. But I think it does leave out the desire some consumers have to purchase domestic. For example, I might be willing to buy a domestically made vehicle if the price is under $25K even if it's more than a similar vehicle made overseas. B…

The idea of the domestically manufactured vehicle is just that, an idea.

There's the fiction of quota and part manifests.

Then there's the reality that, well I assemble a thousand parts in China into one "part" then I import that one "part."

There are a ton of people employed by the autos industry in the US but that's so broad. It basically means there are a ton of people employed by organizing our life around cars. While some are involved in some kind of manufacturing, relative to the amount of manufacturing and manpower in China, it is small.

So every way you look at domestic, it seems less and less like it really means "domestic," and more and more like it's a form of vague but powerful storytelling.

I don't think it's good for anyone to be so wedded to storytelling. And anyway, you could try e-biking in weather, it's fine, sometimes it's even fun, and then suddenly you're like, well do I need more than the occasional rented car?

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#19

Post by a1rb4Ck »

Very cool. Good luck! I used to work on this. Your synthetic dataset pipeline is really neat. A foundation model of molding defects might be feasible. I hope you will also work on the whole inline quality control problem. From what I saw of the field, sometimes you only get the final quality days after painting, finishing or cool down of big parts. And the quality metric is notably undefined for visual defect, using the cad render as a reference is a good solution. Because plastic is so cheap and the process so stable, I have seen days of production shredded for a tiny perfectly repeated visual defects. Injection molding machines are heavily instrumented [0] and I tried to mix in-mold sensors + process parameters + photo + thermography of hot parts [1] (sry it's in french, might find better doc later). [0] https://scholar.google.com/citations?view_op=view_citation&h... [1] https://a1rb4ck.github.io/phd/#[128,%22XYZ%22,85.039,614.438...

Re: Launch HN: Bucket Robotics (YC S24) – Defect detection for molded and cast parts

#20

Post by lasermatts »

a1rb4Ck wrote: post #19

Very cool. Good luck! I used to work on this. Your synthetic dataset pipeline is really neat. A foundation model of molding defects might be feasible. I hope you will also work on the whole inline quality control problem. From what I saw of the field, sometimes you only get the final quality days after painting, finishing or cool down of big parts. And the quality metric is notably undefined for visual defect, using…

Dude yes exactly!!

It's so incredibly frustrating when you're past final assembly of some system, and only then do you see a defect that requires a teardown! You touched upon a really fun piece of defect detection -- quality metrics are highly dependent upon the customer, but that makes it fun for us

Great paper links too, I really appreciate that! My French is a little rusty, but I love the comic at the start!!

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