3DQue’s QuinlyVision Automates 3D Print Failure Detection


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According to Canadian technology startup 3DQue, between 3 and 20% of all print jobs will have defects, or even fail. 3DQue has long been focused on automating 3D printing through its Quinly solution, which combines hardware and software to enable the automation of tasks such as applying adhesives, removing parts, and cleaning the print bed. This allows 3D printers to be capable of continuous, high-volume production without a human operator. Now, the startup is tackling 3D print failures with the launch of its QuinlyVision smart failure detection system.

Driven by artificial intelligence, QuinlyVision has all kinds of cool features, like a built-in troubleshooting guide and customizable automated responses for printing fails. In addition, the system can not only detect, but also correct, 14 different kinds of print failures. The system basically allows 3D printers to be their own supervisors and self-correct their errors, which could enable scalability with very little human input required for reliable printing.

“The excitement of bringing an innovation to life is tempered by fear that the print will fail. Existing technology focuses on detection, not correction,” explained Steph Sharp, the CEO and Co-Founder of 3DQue. “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.”

If you want to pump out high-quality 3D prints time after time, it requires what 3DQue describes as “a delicate interplay of design, calibration and slicing.” Errors are time-consuming, and a waste of money—just think of the filament waste! But it can take even longer to figure out what exactly went wrong, why it happened, and how to fix it; that’s why the “fixmyprint” subreddit has more than 90,000 members. Maybe the bed was too hot, or not hot enough, or maybe your filament took on some moisture, or maybe you just need to change the infill.

QuinlyVision has a built-in Correction Wizard that quickly classifies failures and how they develop, whether it’s an issue with the hardware, the model, or slicing. With this powerful algorithm, users can get detailed 3D print troubleshooting information right away, which will suggest corrections and allow you to set custom automated responses, such as Ignore, Pause, or Notify, for each type of failure you encounter. This enables your 3D printer to self-correct very quickly once it realizes there’s an issue.

“No more guessing,” the website states. “QuinlyVision™ shows where the defect is, what it is called, when it happened, and what action was taken. Whether one print has 5 defects or 5 prints have one defect, QuinlyVision gives you the data you need to correct the problem.”

QuinlyVision recognizes, and can offer auto-corrections, for 14 different print failures, such as under- and over-extrusion, no extrusion, spaghetti, warping, and stringing, and layer shifts. It also knows detach (when your print doesn’t stay put on the bed), nozzle-blob, zits, skirt issues, poor bridging and poor first layer, and if the model is present. Its Subpixel QuinlyVision Technology, or SQUINT, combines object tracking, photogrammetry, AI failure recognition, and subpixel analysis to detect these issues within five seconds.

In addition to its AutoCorrect feature for detecting, responding, and suggesting solutions for those 14 common failures, 3DQue’s new QuinlyVision system has several other great features as well, including:

  • 24/7 unlimited live supervision
  • Secure remote access
  • Open source, meaning compatibility with any 3D printer/camera
  • Easy installation
  • Low light detection

On June 10th, the 3DQue Discord channel showed live testing of the startup’s new QuinlyVision 3D printing failure detection system.

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