Fragility Aware Grasping: With Application to Handling Parts 3D Printed Using Binder Jetting
Abstract In automated de-powdering of binder jetting additive manufactured parts, robots must quickly and accurately calculate how to grasp fragile, brittle green parts without shattering them. Previous work has used non-linear models to find a grasp configuration (specifying the robot gripper position, orientation, and distance between gripper fingers) that minimizes part stress and the likelihood of shattering under the gripper force. However, this process is time-intensive and impractical for additive manufacturing applications, where robots must work quickly. This paper proposes a novel method for accurately and quickly calculating safe grasps for fragile green parts. Our method involves modeling parts using a finite element linear elastic model and calculating part deformation caused by a surface traction force from the gripper’s fingers in each grasp configuration. The grasp configuration resulting in the lowest part deformation is chosen as the least likely to shatter the part. For an elastic and brittle material, part stress is approximately proportional to strain before fracture, meaning the grasp with the lowest strain for the elastic model corresponds to the lowest stress for the brittle part with the same geometry. We integrated our algorithm into a prototype binder jetting de-powdering robot and used the algorithm to choose grasps for binder jetting manufactured green parts. With optimizations such as parallelization, our algorithm takes 18 minutes to calculate grasps per part. During testing, our algorithm’s chosen grasp configuration was used to pick up and hold test green parts without shattering them at 80 N, as measured by the gripper’s contact force sensors, despite the parts shattering under forces as low as 2N in some grasps. Handling fragile green parts is one of the main barriers hindering the automation of the de-powdering process in binder jetting. Our grasping algorithm’s success in enabling the safe handling of green parts will drive progress toward automated de-powdering.
Authors
- Chinedum E. Okwudire
- Alexander Martinez-Marchese (ORCID: https://orcid.org/0000-0002-6722-3386)
- Artyom Boyarov (ORCID: https://orcid.org/0000-0001-9043-7393)
Institutions
- University of Michigan (US)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1115/msec2025-155431
- Primary Topic
- Additive Manufacturing and 3D Printing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00