By Georgia Parsonson
In collaboration with the University of Oregon’s Professor Paul Daulton, researchers from QUT’s Centre in Transformative Biomimetics in Bioengineering have described the potential that artificial intelligence (AI) and machine vision in 3D printers represent within the field of medical implants.
According to the Centre’s Director, Distinguished Professor Dietmar W. Hutmacher, implants and such medical devices as scaffolds – when produced with 3D printing – may be custom made and tailored specifically for each patient.
“In contrast, implants and devices produced through traditional manufacturing methods are usually in standard sizes,” Professor Hutmacher said.
“However, we have several technical challenges to overcome before 3D printing transforms the advanced manufacturing of implants and medical devices.
“Commercially available 3D printers generally offer only high-speed, high-precision, or medical grade bio-materials, and rarely do they offer all three.
“This limits their suitability as a manufacturing platform for medical devices such as biodegradable scaffolds for tissue engineering. The addition of AI and machine vision to 3D printing changes this paradigm.”
This interdisciplinary endeavour has bio-medical engineers – in conjunction with Professor Dalton – working to produce biodegradable, bio-medical designs that have never been printed before, including heart valves, bone scaffolding, and membranes for dental tissue engineering.
According to Professor Hutmacher, “The team is accomplishing this by pairing its melt electrowriting (MEW) printer with machine vision and machine learning systems.
“The vision system comprehensively images the flight path of the extruded fibre to correct errors in real-time, while the machine learning system uses that information to predict the fibre diameter of the scaffold and make more accurate products.
“The processing of high-performance materials such as medical-grade biomaterials for implants is very complex and requires fine-tuning of all process parameters, which is why we monitor the 3D printing process closely.
“By using AI, we can evaluate this data stream and identify hidden printing parameter relationships that are not recognizable to humans.
“This is precisely where the advantage of artificial intelligence lies: it is able to process very large volumes of data quickly, an assignment that is far too monotonous and hence difficult for the human brain.
“Adding machine vision and artificial intelligence (AI) gives the MEW printer the eyes and brains it has so far been missing.
“These new advancements have the potential to transform MEW printers which now will be able to additively manufacture medical devices and implants that have never been printed before.”
Convergence of Machine Vision and Melt Electrowriting was published in Advanced Materials.