3DQue Launches QuinlyVision
Detects 14 failures including warping, layer shift and more.
June 13, 2022
3DQue Systems Inc. reports that its QuinlyVision failure detection system is ready for live testing on 3DQue's Discord.
Packed with features, QuinlyVision offers AutoCorrect3D to detect, automatically respond and suggest solutions to 14 common print failures. By combining AI failure recognition with object tracking, photogrammetry and subpixel analysis, QuinlyVision detects issues in seconds, even in low-light conditions. There are customizable auto response options, a built-in troubleshooting guide, 24/7 unlimited supervision and secure remote access.
“The excitement of bringing an innovation to life is tempered by fear that the print will fail. Existing technology focuses on detection, not correction. Our goal is to provide an elegant solution to simplify failure correction by having QuinlyVision do the legwork—pinpointing the problem, automatically taking action and providing suggestions to prevent future failures,” says co-founder and CEO of 3DQue Steph Sharp.
Quick Diagnostics
By classifying failures and how they develop over time, the built-in Correction Wizard pinpoints root causes such as hardware, slicing or model issues. It provides detailed troubleshooting information on the dashboard.
Autocorrect3D 14 Failures
Like text autocorrect, QuinlyVision's algorithm diagnoses the problem and suggests possible solutions. Autoresponse goes further, allowing different actions (pause, notify or ignore) for each failure type, allowing printers to self-correct the moment an issue is detected.
14 failure types:
- 1. Detach
- 2. Nozzle-Blob
- 3. Skirt
- 4. Under-Extrusion
- 5. Over-Extrusion
- 6. Zits
- 7. Stringing
- 8. Spaghetti
- 9. No-Extrusion
- 10. Warping
- 11. Poor-First-Layer
- 12. Model
- 13. Poor-Bridging
- 14. Layer-Shift
QuinlyVision will be available for live testing in 3DQue's Community Discord starting this week. Limited spots available.
Sources: Press materials received from the company and additional information gleaned from the company’s website.
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