Newly Developed Algorithm Can Correct 3D Printing Errors in Real Time

Scientists from the University of Cambridge have developed what they claim are intelligent 3D printers capable of quickly detecting and correcting errors, no matter the design nor material. More specifically, the engineers were able to develop a machine learning algorithm that can be used with FDM 3D printing to correct printing mistakes in real time. This will not only reduce potential print failures but will also be an accurate and efficient way to automate the 3D printing process.

It goes without saying that monitoring software are becoming a key part of 3D printing processes. Print failures are unfortunately common and are also costly both in terms of money and time. As a result, the ability to control every step of the process is integral when it comes to the continued industrialization of additive manufacturing. And at the same time, users are also looking for greater automation in order to enable 3D printing at scale. This is where algorithms, especially those based on machine learning, come in as outlined in the article Generalisable 3D printing error detection and correction via multi-head neural networks.

An example image of the 3D printer nozzle with the highlighted images showing where the algorithm is focusing (photo credits: Douglas Brion)

A “Driverless” Algorithm for 3D Printing

The machine learning algorithm was developed by Douglas Brion and Sebastian Pattinson by training a deep learning computer model. This was done by showing it about 950,000 images that had been captured automatically during the production of 192 printed parts. Each image was labelled with the printer settings used during the print, for example speed and temperature of the printing nozzle, as well as how far those were from what the ideal settings would have been. This enabled the algorithm to then learn how to fix these mistakes rather than relying on humans who are not as adept as identifying them.