Accelerated discovery of 3D printing materials using data-driven multiobjective optimization
Publication
SCIENCE ADVANCES
Authors
T. Erps, M. Foshey, M. K. Luković, W. Shou, H. H. Goetzke, H. Dietsch, K. Stoll, B. von Vacano, W. Matusik
Abstract
In this work, we propose a semiautomated data-driven workflow for finding new photocurable inks for additive manufacturing. The semiautomated pipeline is developed to be cost-effective and efficient for finding 3D printing materials; however, a completely autonomous system is possible with certain robotic manipulators. The aim of the workflow is to find a set of best composite formulations composed of six primary formulations of photocurable inks to improve the mechanical properties beyond the performance levels of primary formulations designed by hand. These composite formulations are automatically optimized for multiple performance objectives with a limited amount of experiments performed.