Researchers from the Washington State University (WSU) School of Mechanical and Materials Engineering developed an AI technique called Bayesian Optimization to find the optimum 3D printing settings the team needed to recreate lifelike 3D-printed models of human organs. While this may sound simple, the group needed to determine a multitude of variables to find the best solution, and finding the best setup could take a lot of time.
These include looking for the most suitable materials, 3D printing configurations, nozzle pressure, and more. “The sheer number of potential combinations is overwhelming, and each trial costs time and money,” Associate Professor Jana Doppa of Computer Science at WSU told Tech Xplore.
