Hi everyone,
As part of my dissertation for my Computer Science degree at Newcastle University, I investigated how to enhance the current state of 3D print failure detection. Current approaches such as Obico’s “Spaghetti Detective” utilise a vision based machine learning model, trained to only detect spaghetti related defects with a slow throughput on edge devices (<1fps on 2Gb Raspberry Pi 4b), making it not edge deployable, real-time or able to capture a wide plethora of defects. Whilst their model can be inferred locally, it’s expensive to run, using a lot of compute, typically inferred over their paid cloud service which introduces potential privacy concerns.
My research led to the creation of a new vision-based ML model, focusing on edge deployability so that it could be deployed for free on cheap, local hardware. I used a modified architecture of ShuffleNetv2 backbone encoding images for a Prototypical Network to ensure it can run in real-time with minimal hardware requirements (averaging 15FPS on the same 2Gb Raspberry Pi, a >40x improvement over Obico’s model). My benchmarks also indicate enhanced precision with an averaged 2x improvement in precision and recall over Spaghetti Detective.
My model is completely free to use, open-source, private, deployable anywhere and outperforms current approaches. To utilise it I have created PrintGuard, an easily installable PyPi Python package providing a web interface for monitoring multiple different printers, receiving real-time defect notifications on mobile and desktop through web push notifications, and the ability to link printers through services like Octoprint for optional automatic print pausing or cancellation, requiring <1Gb of RAM to operate. A simple setup process also guides you through how to setup the application for local or external access, utilising free technologies like Cloudflare Tunnels and Ngrok reverse proxies for secure remote access for long prints you may not be at home for.
Whilst feature rich, the package is currently in beta and any feedback would be greatly appreciated. Please use the below links to find out more. Let's keep failure detection open-source, local and accessible for all!
📦 PrintGuard Python Package - https://pypi.org/project/printguard/
🎓 Model Research Paper - https://github.com/oliverbravery/Edge-FDM-Fault-Detection
🛠️ PrintGuard Repository - https://github.com/oliverbravery/PrintGuard
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