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Making 3D Printing Smarter with Machine Learning


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A 3-D Printed Ball

Printfixer is a new machine learning driven software package that will make 3-D printing 50% more accurate

Credit: PXHERE

University of Southern California (USC) Viterbi School of Engineering researchers have spent six years developing machine learning three-dimensional (3D) printing software to improve printing accuracy by 50% or more.

The PrintFixer software facilitates convolution modeling of 3D printing, with the goal of creating an artificial intelligence (AI) model that precisely predicts shape deviations for all types of 3D printing. PrintFixer employs data collected from previous printing jobs to train its AI to predict where shape distortion will occur, and correct print errors before they happen.

USC Viterbi's Nathan Decker said, "Once we get a lot of people around the world using this, all of a sudden, you have a really incredible opportunity to leverage a lot of data, and that could be a really powerful thing."

From USC Viterbi News 
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA


 

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