I Automated Pressure Advance Using a Bed-Leveling Sensor — CNC Kitchen

Why this is in the vault

Stefan demonstrates that the load cell already embedded in Prusa printers for bed probing can be repurposed — via a custom web tool + open-source G-code sweep — to automatically determine the correct Pressure Advance (K) value without printing a calibration object. The same sensor can also auto-determine maximum volumetric flow rate, detect skew, and flag extrusion anomalies. The core argument — "the hardware is already there; smarter software unlocks entirely new capabilities" — applies beyond 3D printing and is a recurring theme in RDCO's digital manufacturing intelligence track.

Episode summary

Modern high-speed 3D printers depend on Pressure Advance (PA / K value) compensation to prevent over- and under-extrusion at corners during rapid speed changes. Manual calibration requires printing test patterns and visual inspection — material-dependent and tedious to repeat per filament. Bambu Lab automated this first (X1 via LiDAR scanner, newer models via a hotend force sensor), but the rest of the industry hasn't followed despite having the necessary hardware.

Stefan built an open-source web tool that connects to a Prusa Nextruder's load cell via the printer's OpenMetrics network interface. The tool runs a slow→fast→slow extrusion sweep at increasing K values and records the force response. Key finding: the clearest reliable signal is the undershoot — when the force dips below steady-state after switching from high to low extrusion rate, that indicates over-compensation (K too high). The optimal K is the last value before undershoot appears. Results matched manual calibration closely across several materials.

The video also covers Bamboo Lab patent landscape: camera-based calibration (X1 LiDAR) is patented in CN/US/EU; force-based calibration is patented in China but the international PCT application appears not to have been successfully pursued in Europe as of July 2026 — leaving a patent gap that could allow open-source Klipper implementation.

Key arguments / segments

• [00:00:04] — Intro framing: bed-leveling sensors are massively underutilized; thesis stated.

• [00:01:42] — Physics explainer: extrusion system as a spring; why PA compensation is needed at high speed.

• [00:03:38] — Traditional calibration: print test patterns, visual inspection, per-filament tuning problem.

• [00:05:50] — Prusa Nextruder load cell intro; Snapmaker U1 as existence proof of force-based auto-calibration. Sponsor segment (Zellerfeld job listing).

• [00:07:38] — Snapmaker U1 Klipper code analysis: slow-fast-slow extrusion pattern is visible but evaluation algorithm is proprietary/closed.

• [00:09:48] — Prusa OpenMetrics interface; custom web tool recording live load cell data; square-wave force response visualization.

• [00:11:54] — Web tool demo: G-code generation, K-value sweep, metrics calculated (overshoot, undershoot, slope, settling, error area).

• [00:13:33] — Key finding: undershoot metric is most robust. Results vs. manual calibration: close match across materials, slight high bias, ASA outlier.

• [00:15:23] — Open-source release; second sensor application: maximum volumetric flow rate sweep (already implemented in tool).

• [00:17:37] — Process monitoring vision: per-print report on temperature stability, extrusion response, crash/clog detection. Current QC is "look at the outside" — inadequate for structural parts.

• [00:19:10] — Bamboo Lab patent landscape: camera-based = protected CN/US/EU; force-based = CN patent, PCT not pursued in EU — potential opening for open-source Klipper implementation.

• [00:20:55] — Conclusion: hardware already exists, smarter software unlocks it. Project open-source on GitHub.

Credibility notes

• Stefan Herrmann is an engineer-practitioner; builds and tests real hardware rather than reporting secondhand.
• Sample size for validation is limited (handful of materials); acknowledges the method needs more tuning.
• Patent analysis comes with explicit "not a lawyer" caveat — treat as directional, not legal opinion.
• Zellerfeld sponsorship is well-disclosed and highly relevant to the video topic (they hire the audience).

Mapping against Ray Data Co

Mapping: weak — The digital manufacturing discovery track is the reason this video belongs in the vault, not a direct RDCO business application. That said, the architectural insight generalizes:

• Sensor reuse pattern: Existing hardware (load cell) unlocked via better software — directly analogous to enterprise "dark data" or underutilized telemetry that RDCO clients often have. The framing "the hardware is already there" is a consulting wedge argument.
• Open-source proof-of-concept → firmware integration gap: Stefan's web tool is a PoC that works but would be better as native firmware. This mirrors the "demo vs. production" gap RDCO navigates in client AI deployments.
• Patent moat analysis: Bamboo Lab's IP strategy (protect camera-based, leave force-based partially open) is a decent case study in calibrated patent defense for hardware+software companies — relevant if RDCO ever advises manufacturing clients on IP strategy.
• Direct operational use: None. RDCO does not manufacture or resell printers.

Related

• [[06-reference/2026-07-11-cnc-kitchen-bumpmesh-is-better]] — prior CNC Kitchen entry; computational geometry tool built open-source by Stefan; similar "small tool, outsized impact" pattern
• [[06-reference/2026-06-20-cnc-kitchen-laser-3d-printing-solution]] — CNC Kitchen xTool laser review; adjacent digital manufacturing coverage
• [[06-reference/2026-06-01-cnc-kitchen-bambu-a2l-review]] — Bambu Lab A2L review; provides context on the Bambu ecosystem Stefan references throughout this video
• [[01-projects/digital-manufacturing-discovery/2026-04-19-channel-shortlist]] — channel shortlist that positioned CNC Kitchen as primary depth source for operational 3D printing intelligence

Sponsorship

Sponsored by Zellerfeld (Hamburg-based 3D-printed footwear manufacturer). Stefan has a genuine prior relationship — he previously visited and documented their production facility. Sponsor segment (~00:05:01–00:07:01) promotes a software engineer job opening; the content is directly relevant to the video's technical audience. Disclosure is clear and upfront.