fastener counter

Fastener Fusion: Automating The Art Of Counting

Counting objects is an ideal task for automation, and when focusing on a single type of object, there are many effective solutions. But what if you need to count hundreds of different objects? That’s the challenge [Christopher] tackled with his latest addition to his impressive automation projects. (Video, embedded below.)

[Christopher] has released a series of videos showcasing a containerized counting system for various fasteners, available on his YouTube channel. Previously, he built remarkable devices to count and sort fastener hardware for automated packaging, but those systems were designed for a single fastener type. He effectively highlights the vast complexity of the fastener ecosystem, where each diameter has dozens of lengths, multiple finishes, various head shapes, and more.

To address this, he developed a machine that accepts standardized containers of fastener hardware. These uniform boxes can hold anything from a small M2 countersunk screw to a large M8 cap head bolt and everything in between. To identify the loaded box and determine the appropriate operations, the machine features an RFID reader that scans each box’s unique tag.

Once a box is loaded, the machine tilts it to begin counting fasteners using a clever combination of moving platforms, an optical sensor, and gravity. A shelf first pushes a random number of fasteners onto an adjustable ledge. A second moving platform then sweeps excess fasteners off, leaving only those properly aligned. It’s no surprise this system has nine degrees of freedom. The ledge then moves into view of a sensor from a flatbed scanner, which detects object locations with an impressive 0.04 mm resolution across its length—remarkable for such an affordable sensor. At this point, the system knows how many fasteners are on the ledge. If the count exceeds the desired number, a sloped opening allows the ledge to lift just high enough to release the correct amount, ensuring precision.

The ingenuity continues after the initial count. A secondary counting method uses weight, with a load cell connected to the bin where fasteners drop. A clever over-center mechanism decouples the tilting system from the load cell to ensure accurate readings. We love automation projects, and this one incorporates so many ingenious design elements that it’s sure to inspire others for their future endeavors.

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Hackaday Links: July 6, 2025

Taking delivery of a new vehicle from a dealership is an emotional mixed bag. On the one hand, you’ve had to endure the sales rep’s hunger to close the deal, the tedious negotiations with the classic “Let me run that by my manager,” and the closer who tries to tack on ridiculous extras like paint sealer and ashtray protection. On the other hand, you’re finally at the end of the process, and now you get to play with the Shiny New Thing in your life while pretending it hasn’t caused your financial ruin. Wouldn’t it be nice to skip all those steps in the run-up and just cut right to the delivery? That’s been Tesla’s pitch for a while now, and they finally made good on the promise with their first self-driving delivery.
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Diagnosing Whisker Failure Mode In AF114 And Similar Transistors

The inside of this AF117 transistor can was a thriving whisker ecosystem. (Credit: Anthony Francis-Jones)
The inside of this AF117 transistor can was a thriving whisker ecosystem. (Credit: Anthony Francis-Jones)

AF114 germanium transistors and related ones like the AF115 through AF117 were quite popular during the 1960s, but they quickly developed a reputation for failure. This is due to what should have made them more reliable, namely the can shielding the germanium transistor inside that is connected with a fourth ‘screen’ pin. This failure mode is demonstrated in a video by [Anthony Francis-Jones] in which he tests a number of new-old-stock AF-series transistors only for them all to test faulty and show clear whisker growth on the can’s exterior.

Naturally, the next step was to cut one of these defective transistors open to see whether the whiskers could be caught in the act. For this a pipe cutter was used on the fairly beefy can, which turned out to rather effective and gave great access to the inside of these 1960s-era components. The insides of the cans were as expected bristling with whiskers.

The AF11x family of transistors are high-frequency PNP transistors that saw frequent use in everything from consumer radios to just about anything else that did RF or audio. It’s worth noting that the material of the can is likely to be zinc and not tin, so these would be zinc whiskers. Many metals like to grow such whiskers, including lead, so the end effect is often a thin conductive strand bridging things that shouldn’t be. Apparently the can itself wasn’t the only source of these whiskers, which adds to the fun.

In the rest of the video [Anthony] shows off the fascinating construction of these germanium transistors, as well as potential repairs to remove the whisker-induced shorts through melting them. This is done by jolting them with a fairly high current from a capacitor. The good news is that this made the component tester see the AF114 as a transistor again, except as a rather confused NPN one. Clearly this isn’t an easy fix, and it would be temporary at best anyway, as the whiskers will never stop growing.

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Pretty purple PCBs, made in the USA

Does Made-in-America Make Sense For PCB Prototyping?

These are tough times for American hackers, and rife with uncertainty. Trade wars are on, off, on again– who can keep track? If you’re used to getting everything from China, that can really cramp your style. [Jeremy Cook] took the time to write up his experience prototyping with American-made PCBs, just in time for us to totally miss Independence Day.

The project was a simple nightlight, using a single LED, a photoresistor, a transistor, and a CR2032 battery. The CR2032 battery does complicate things, though: [Jeremy] figured out a neat way to hold the battery using a PCB cutout, but it needs to be a 0.8 mm board. (That’s going to matter in a moment.) He’s put that PCB on GitHub if you’re interested.

To start off, JLBPCB is the Chinese clearing house of choice for [Jeremy], and they quoted a very cheap $7.10 for 20 boards. The problem was that shipping across the Pacific Ocean, plus the ever-wavering tariff charge, brought the price to $48.08. About five dollars of which was from tariffs; the rest you can put down to the cost of jet fuel and the size of the Pacific Ocean.

On the other hand, OSH Park, was able to get [Jeremy] three of their pretty purple PCBs for $7.75 all-inclusive. Overall, since he’s prototyping and does not want 20 boards this revision, [Jeremy] saves quite a lot by staying local– including the environmental impact of shipping and laxer regulations in China, if that sort of thing matters to you. 

The suprizing thing is the turnaround time: [Jeremy] got his pretty purple PCBs from OSH Park a full twenty days after ordering. Similar orders from China take only a week, which is just mind-blowing when you stop and think about the great honking ocean in the way. We could perhaps cut OSH Park some slack in that 0.8 mm boards are not the most common, but their quoted turnaround time for two-layer prototypes is minimum 12 days.

They do offer a “super-swift” option for two-layer boards, but then they lose on price. As [Jeremy] points out, there are always tradeoffs. If you’re really in a hurry, nothing’s faster than milling the boards yourself. Or you could go the old-school toner-transfer etching route.

Our thanks to [Jeremy] for the tip. If you’ve got a better way to prototype, do send us a tip about it. Also, please us know in the comments if you’ve tried an in-country PCB fabricator, and how it compared to the usual offerings from the PRC.

Visiting Our Neighbor Sedna: Feasibility Study Of A Mission To This Planetoid

Image of Sedna, taken by the Hubble Space telescope in 2004. (Credit: NASA)
Image of Sedna, taken by the Hubble Space telescope in 2004. (Credit: NASA)

While for most people Pluto is the most distant planet in the Solar System, things get a lot more fuzzy once you pass Neptune and enter the realm of trans-Neptunian objects (TNOs). Pluto is probably the most well-known of these, but there are at least a dozen more of such dwarf planets among the TNOs, including 90377 Sedna.

This obviously invites the notion of sending an exploration mission to Sedna, much as was done with Pluto and a range of other TNOs through the New Horizons spacecraft. How practical this would be is investigated in a recent study by [Elena Ancona] and colleagues.

The focus is here on advanced propulsion methods, including nuclear propulsion and solar sails. Although it’s definitely possible to use a similar mission profile as with the New Horizons mission, this would make it another long-duration mission. Rather than a decades-long mission, using a minimally-equipped solar sail spacecraft could knock this down to about seven years, whereas the proposed Direct Fusion Drive (DFD) could do this in ten, but with a much larger payload and the ability do an orbital insertion which would obviously get much more science done.

As for the motivation for a mission to Sedna, its highly eccentric orbit that takes it past the heliopause means that it spends relatively little time being exposed to the Sun’s rays, which should have left much of the surface material intact that was present during the early formation of the Solar System. With our explorations of the Solar System taking us ever further beyond the means of traditional means of space travel, a mission to Sedna might not only expand our horizons, but also provide a tantalizing way to bring much more of the Solar System including the Kuiper belt within easy reach.

Going To The (Parallel) Chapel

There is always the promise of using more computing power for a single task. Your computer has multiple CPUs now, surely. Your video card has even more. Your computer is probably networked to a slew of other computers. But how do you write software to take advantage of that? There are many complex systems, of course, but there’s also Chapel.

Chapel is a reasonably simple programming language, but it supports parallelism in various forms. The run time controls how computers — whatever that means — communicate with one another. You can have code running on your local CPUs, your GPU, and other processing elements over the network without much work on your part.

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Convert Any Book To A DIY Audiobook?

If the idea of reading a physical book sounds like hard work, [Nick Bild’s] latest project, the PageParrot, might be for you. While AI gets a lot of flak these days, one thing modern multimodal models do exceptionally well is image interpretation, and PageParrot demonstrates just how accessible that’s become.

[Nick] demonstrates quite clearly how little code is needed to get from those cryptic black and white glyphs to sounds the average human can understand, specifically a paltry 80 lines of Python. Admittedly, many of those lines are pulling in libraries, and some are just blank, so functionally speaking, it’s even shorter than that. Of course, the whole application is mostly glue code, stitching together other people’s hard work, but it’s still instructive and fun to play with.

The hardware required is a Raspberry Pi Zero 2 W, a camera (in this case, a USB webcam), and something to hold it above the book. Any Pi with the ability to connect to a camera should also work, however, with just a little configuration.

On the software side, [Nick] pulls in the CV2 library (which is the interface to OpenCV) to handle the camera interfacing, programming it to full HD resolution. Google’s GenAI is used to interface the Gemini 2.5 Flash LLM via an API endpoint. This takes a captured image and a trivial prompt, and returns the whole page of text, quick as a flash.

Finally, the script hands that text over to Piper, which turns that into a speech file in WAV format. This can then be played to an audio device with a call out to the console aplay tool. It’s all very simple at this level of abstraction.

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