Vectric Tool Database based off IDC Woodcraft Tool Database

LowRider CNC Your Builds
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LR4_CHIPLOAD_SYSTEM.zip (230.1 KB)

LR4 Chipload Tool Library (Simple Reference)

I’ve been working on my tool database for the LowRider 4 and ended up rebuilding it around chipload instead of fixed feeds.

:brain: Idea

Feeds are based on:
Feed = RPM × Flutes × Chipload
Then scaled for LR4 (~0.7) → using mm/sec

:+1: What I noticed

  • more consistent cuts

  • fewer issues with burning or melting

  • tools scale more predictably (1/4", 1/8", etc.)

  • less trial and error overall

:wrench: Why it might help

This isn’t tied to VCarve—just a chipload-based approach, so it can be used in other CAM software too.

AI tools can also adapt this pretty easily to:

  • other CAM programs

  • different machines

  • different unit setups

:gear: What I’m using (for reference)

  • Chipload range: ~0.03–0.065 mm depending on material/tool

  • RPM: 18,000 (wood) / 16,000 (acrylic)

  • Flutes: 2

  • Units: mm/sec

  • LR4 scaling factor: ~0.7

Depth of cut:

  • ~30% of diameter (wood)

  • ~25% (acrylic)

Plunge:

  • ~40–45% of feed

:bullseye: Goal

Mostly sharing this in case it helps other LR4 builders—new or experienced.
Just a solid starting reference instead of guessing feeds from scratch.

The above is a summary from ChatGPT. It’s a baseline tool database based on the IDC Woodcraft database, with numbers tuned for the LowRider 4.

AI should be able to adapt this reference pretty easily to other CAM software as well.

These numbers were derived from AI’s understanding of the LowRider 4.

If you have any questions or concerns, feel free to ask—I’ll pass them along to AI lol

1 Like
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In the future, skip the LLM summary or put it in a “Hide Details” tag. I really want to know what you think. If I wanted a chat gpt summary, I could do it myself.

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Not to jump on anyone, but this is a dangerous way to think about AI. It has no “understanding,” it is recombining what other people have said about a given topic providing weight on what to include by what it’s model shows as having been repeated most often. Do not fall into the trap of anthropomorphizing these services.

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I reviewed and use the settings they are conservative. I had AI modify the values that help fit the machine. There are 5 material settings with very conservative settings.

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Ai stuff mostly eran a flag or not to read from most users.

The info is helpful for someone who hasn’t done the job already but: testing tourself for the values is the right approach.