“You can optimize the results, saving time, cost and labor,” said Kaiyan Qiu, co-corresponding author on the paper and Berry Assistant Professor in the WSU School of Mechanical and Materials Engineering.
Washington State University study
In this study, the researchers designed a principled methodology which aimed at identifying optimal direct ink writing (DIW) 3D printing input parameters for manufacturing different presurgical organs.
Bayesian optimization (BO) is a powerful machine learning technique for optimizing complex, expensive, black-box objective functions.
The process consists of four steps, the first of which is input generation through a BO algorithm which sets the input parameters for 3D printing. This is followed by the actual 3D printing of the organ.