  With the rapid rise of 3D-printing as a competitive mass manufacturing
method, manual "decaking" - i.e. removing the residual powder that sticks to a
3D-printed part - has become a significant bottleneck. Here, we introduce, for
the first time to our knowledge, a robotic system for automated decaking of
3D-printed parts. Combining Deep Learning for 3D perception, smart mechanical
design, motion planning, and force control for industrial robots, we developed
a system that can automatically decake parts in a fast and efficient way.
Through a series of decaking experiments performed on parts printed by a Multi
Jet Fusion printer, we demonstrated the feasibility of robotic decaking for
3D-printing-based mass manufacturing.
