Washington State University researchers use AI to optimize 3D print settings.
A new machine learning algorithm has enabled researchers at Washington State University (WSU) to improve 3D printing efficiency for manufacturing intricate structures.
According to the researchers, this could allow for more seamless use of 3D printing for complex designs in everything from artificial organs to flexible electronics and wearable biosensors. As part of the study, the algorithm learned to identify and then print the best versions of kidney and prostate organ models, printing out 60 continually improving versions.
“You can optimize the results, saving time, cost and labor,” said Kaiyan Qiu, co-corresponding author on the paper and professor in the WSU School of Mechanical and Materials Engineering.
For engineers, trying to develop the correct settings for 3D printing projects can be cumbersome and inefficient. “The sheer number of potential combinations is overwhelming, and each trial costs time and money,” said Jana Doppa, co-corresponding author and a professor of computer science at WSU.
Qiu has done research for several years in developing complex, lifelike 3D-printed models of human organs. These can be used to train surgeons or evaluate implant devices but the models have to include the mechanical and physical properties of the real-life organ, including veins, arteries, channels and other detailed structures.
Qiu, Doppa, and their students used multi-objective Bayesian Optimization to find the most efficient 3D print settings. Using this technique, the researchers were able to optimize three different objectives for their organ models: the geometry precision of the model, its weight or how porous it is and the printing time.
“It’s hard to balance all the objectives, but we were able to strike a favorable balance and achieve the best possible printing of a quality object, regardless of the printing type or material shape,” said co-first author Eric Chen, a WSU visiting student working in Qiu’s group.
Alaleh Ahmadian, co-first author and WSU graduate student in the School of Electrical Engineering and Computer Science, added that the researchers were able to look at all the objectives in a balanced manner for favorable results and that the project benefited from its interdisciplinary perspective.
“It is very rewarding to work on interdisciplinary research by performing physical lab experiments to create real world impact,” she said.
The researchers first had the computer program print out a surgical rehearsal model of a prostate. Because the algorithm is broadly generalizable, they could easily change it with small tunings to print out a kidney model.
“That means that this method can be used to manufacture other more complicated biomedical devices, and even to other fields,” said Qiu.
The research is published in Advanced Materials.
