On March 20th 2019, after more than two year’s collaborative efforts with Dr. Wenchao Zhou, an Assistant Professor from the Department of Mechanical Engineering at the UA and the startup company AMBOTS, we made the world-first cooperatively 3D-printed part. It is the first time that multiple independent 3D printers work together to print a part with a size way bigger than the printer itself. This achievement is realized through our Swarm Printing concept and the cooperative 3D printing (C3DP) platform. The workpiece (a beehive structural beam) shown in the picture is approximately 840×70×20 mm in L×W×H. The workpiece in this size would be impossibly printed by any existing commercial desktop 3D printers. The C3DP platform is backed by several research methods and technologies developed by the team, including 3D printing robotics, chunk-based slicer, chunk bond strength testing, and automatic scheduling and path planning for chunk-based C3DP. Our vision is to establish an Autonomous Digital Additive Manufacturing (ADAM) system of the future. On March 21st, we demonstrated our research and technologies to the R&D group of ArcBest. See media coverage on our project here.
Our research on cooperative 3D printing, especially our recent efforts on developing a new computational framework for automatically generating scheduling strategies of coordinating a swarm of printing robots was recently highlighted by Research Frontiers at the University of Arkansas. This project is collaborated with Dr. Wenchao Zhou from the Department of Mechanical Engineering at the UA and the startup company AMBOTS. Please see SiDi Publication and our previous post for details. The work has been also highlighted in several mainstream media of 3D printing industry, such as 3dprint.com, 3dprintingindustry.com, and all3dp. It was also recently listed as one of the five coolest things on the earth in the fourth week of May by GE reports.
SiDi Lab recently received a seed grant for initiating an industrial collaboration with Ford Motor Company. This grant is awarded by the Office of Research & Innovation at the University of Arkansas. We will collaborate with Ford Global Data, Insight & Analytics (GDIA) to establish a novel approach to modeling customer choice behaviors in electric vehicle (EV) market based on network theory. Particularly, we will investigate how well the network model performs in predicting customers’ choices in EV market as compared to existing choice modeling techniques, such as the Discrete Choice Model.