How We Source and Normalize Diode Laser Settings
Every number on this site comes from a real, attributable source — manufacturer documentation, LightBurn library data, or a named community result. When we derive a setting by calculation, we label it explicitly. This page explains the full pipeline: sourcing tiers, the wattage normalization formula, confidence labels, and how to read a settings table.
Why We Built a Methodology at All
Most settings resources online are one of two things: manufacturer-provided tables (accurate for that specific machine, thin on coverage) or forum posts (potentially accurate, but with no machine spec, no repeatability context, and no way to know if the poster even succeeded). Both are useful; neither is structured.
The approach here is to aggregate both, tag every number with its origin, normalize across machine wattages using a documented formula, and publish ranges rather than single values — because laser results are inherently variable and pretending otherwise misleads people.
We do not own a fleet of laser machines. We cannot run first-party tests. Claiming we did would be lying. The honest alternative is transparent aggregation: you know exactly where every number came from, you can go verify it yourself, and you know what confidence to place in it.
Source Tiers
Every row in every settings table carries a source_type tag from one of four tiers, listed here from highest to lowest confidence.
Tier A — Manufacturer Official (Confidence: High)
Settings published directly by xTool, Sculpfun, Ortur, Atomstack, or the laser manufacturer on their own website, in product documentation, or in their official support materials. These are the most reliable anchor points — the company has run the test on their own hardware.
Coverage is thin. Manufacturers typically publish settings for a handful of materials at one or two wattages. We fetch these directly from their HTML pages when available. We cannot read proprietary binary formats like LightBurn's .clb files; a source tagged Tier A comes from a real, crawlable URL.
Tier B — LightBurn Community Library (Confidence: High / Medium)
LightBurn maintains a community materials library. Where individual entries in this library are accessible via a crawlable URL or published export, we use them as Tier B sources. These have been submitted and used by real people on real hardware.
The LightBurn app is largely binary and not web-crawlable. We do not claim to have read .clb files or the in-app library. Only entries with a real, verifiable web reference qualify as Tier B.
Tier C — Derived-Scaled (Confidence: Medium — "Calculated Starting Point")
When we have a verified Tier A or B setting for one machine wattage, we can calculate an equivalent starting point for a different wattage using the energy-equivalence relationship. This is the most common way to fill cross-wattage gaps.
The formula:
Energy delivered per unit area ∝ Power / Speed. To deliver the same effective energy with a different optical wattage:
new_speed = old_speed × (new_watts / old_watts)
new_power_pct ≈ old_power_pct × (old_watts / new_watts), clamped 1–100%
Both approaches are equivalent; use whichever keeps the percentage within a useful range.
This formula is approximate. It assumes the two modules have similar beam quality (M² factor) and focus spot size, which is roughly true for machines in the same class but not guaranteed. Derived settings are labelled as "calculated starting point" — they are a better beginning than a random guess but require more dialling-in than Tier A data.
Hard limits on Tier C use: Derived rows may not be the majority of any published settings page. A page that is entirely derived from a single anchor point is not published as a standalone URL — it would be one real data point dressed up as eight, which is not informative.
Tier D — Community-Verified (Confidence: Low)
Named, linked results from community members — a specific Reddit post, a forum thread with a photo and machine spec, a YouTube video where someone shows the result with settings visible. We quote and link; we never silently average forum threads.
The key distinction: a Tier D entry requires a specific named source we can link to. "People on Reddit generally seem to use around 500 mm/min" is not a Tier D entry — it is anonymous hearsay and does not belong on this site. "u/SomePerson on r/diylasers reported 450 mm/min, 70% power, one pass, confirmed clean cut in photo" is a Tier D entry.
Confidence Labels
Settings tables display confidence at the row level:
| Label | What it means | How much to trust it |
|---|---|---|
| High | Manufacturer official or verified library entry | Close starting point; still run a test |
| Medium | Derived from a high-confidence anchor, or Tier D with corroboration | Good starting point; expect to tune ±20% |
| Low | Single uncorroborated community report | Use as a rough order of magnitude; run a test grid first |
| Single-source | Only one data point exists (flagged explicitly) | Treat as anecdote; verify yourself |
Why Ranges, Not Point Values
Most settings tables online give a single number: "Speed: 500 mm/min, Power: 80%." That number implies false precision. The actual workable range for most material-operation combinations spans ±15–30% — because material batches vary, moisture content varies, lens condition varies, and "80% power" on one machine controller may not equal 80% optical output on another.
We publish result ranges wherever the sourcing permits it. A range of 400–600 mm/min is more honest than 500 mm/min and more useful — you know the centre of gravity, you know how much latitude you have, and you don't have to wonder whether 520 mm/min is safe to try.
When only a single data point exists, we publish it as a single value with a single-source confidence label and explicitly note it needs verification.
Speed Units
Speeds are stored internally in mm/min (millimetres per minute) and displayed in both mm/min and mm/s on every page. LightBurn defaults to mm/min; LaserGRBL uses mm/min; most GRBL documentation uses mm/min. The conversion is: mm/s = mm/min ÷ 60.
If you're entering settings into software that uses a different unit, always check which unit the field expects. Entering "500" in an mm/s field when you mean mm/min is a 30× speed difference and will produce very different results.
The Wattage Normalization Model
The most original contribution this site makes is cross-machine normalization. For a given material and operation, we build a wattage curve: how does the optimal power/speed combination shift as you move from a 5W machine to a 10W, 20W, 33W, or 40W machine?
The model uses the energy-equivalence formula above as its backbone, anchored by Tier A data points wherever they exist, and validated against Tier D community results where they're available for multiple wattages. The normalization report — showing the full cross-machine comparison with all inputs attributed — is published separately and is the only artifact on this site that makes a genuinely citable methodological contribution.
Freshness and Verification Dates
Every settings page shows a "Last verified" date. This date reflects when we last checked source URLs for availability and confirmed the referenced settings are still current. Sources go dead; manufacturers update their recommendations; community posts get deleted.
If you find a dead source link, that is a signal that the data needs re-verification, not that the data is wrong — but treat it with lower confidence until a live source is confirmed.
What We Do Not Publish
- Unattributed numbers. If a setting can't be linked to a real source, it doesn't appear on the site.
- Results we fabricated. There is no "tested by our team" tier because we don't have a testing team with machines. Any page claiming first-party tests from this site would be lying.
- Pages that are entirely derived from one anchor. One real data point produces one table row, not a full standalone page.
- Silent forum averages. Community data appears only when we can link to a specific named result.
AI-Assisted Production Disclosure
This site is produced with AI assistance. Page generation, data sourcing pipelines, and structural formatting are partially automated. This does not change the sourcing requirements — every number still requires a real, attributed source. AI is used to maintain consistent structure and attribution across a large database, not to invent numbers.
The normalization model, the confidence framework, and the sourcing pipeline are human-designed and documented here. AI executes the pipeline; the methodology is ours.
How to Use This in Practice
When you load a settings page:
- Find the row for your machine's optical wattage (not nominal wattage — the number of real watts at the lens).
- Check the confidence label. High = start there. Low = treat as rough guidance and run a test grid.
- Note the source reference and when it was last verified.
- For cutting operations, run a test grid (use the generator) before cutting final material.
- Start at the middle of the published range, adjust based on your first test results.
The goal is to get you to a clean result in fewer test cuts, not to save you from doing any testing at all.