Process planning solution strategies for fabrication of thin-wall domes using directed energy deposition

ABSTRACT

Although multi-axis bead deposition-based additive manufacturing processes have been investigated in many aspects in the literature, a general process planning approach to address collision detection and prevention still needs to be developed to fabricate complex thin-wall geometries in a supportless fashion. In this research, an algorithm is presented that partitions the surfaces of the part and finds the appropriate tool orientation for each partition to avoid collisions.¹ This algorithm is applied to segment the surface of a thin-wall hemisphere dome and fabricate it without the need of support structures. Two main fabrication strategies are developed: wedge-shaped partitioning, and a rotary toolpath. A five-axis toolpath and a 2 + 1 + 1-axis toolpath is introduced to fabricate the partitioned build scenarios. A rotary (1 + 3-axis) toolpath is also developed. Tool paths are developed, and the domes built using a directed energy deposition process. The built geometry aligns well with the process planning solutions, but material build up is observed at the partition interfaces. Planar slicing is used to generate toolpaths. However, it is concluded that planar slicing brings limitations to reduce the number of partitions that can be modified by a constant-step-over toolpath.

KEYWORDS:

• Additive manufacturing
• surface dome
• collision-free
• multi-axis direct energy deposition

Acknowledgments

Special thanks to CAMufacturing Solutions, Inc. (especially Bob Hedrick) for their financial and technical support as well as using their developed software APLUS. Thanks to Lincoln Laser solutions for their technical support. Thanks to Mitacs Accelerate for financial support.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. A shorter version of this paper was presented at the IFAC IMS 2019, May-13 (Kalami and Urbanic 2019).

Additional information

Funding

This work was supported by the Mitacs [IT12867]; Mitacs [IT07050].