Automated Build Orientation and Substrate Optimization for Multi-Axis Hybrid Additive Manufacturing
Open Access
- Author:
- Walsh, Christopher
- Graduate Program:
- Engineering Science and Mechanics
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- October 27, 2021
- Committee Members:
- Albert Segall, Program Head/Chair
Edward William Reutzel, Thesis Advisor/Co-Advisor
Sanjay Joshi, Thesis Advisor/Co-Advisor
Abdalla Ramadan Nassar, Committee Member - Keywords:
- AM
Additive Manufacturing
Hybrid Manufacturing
HM
Automation
Decomposition
Substrate Optimization
Multi-Axis
5-Axis
Orientation - Abstract:
- Multi-axis hybrid manufacturing (HM) machines combine the capabilities of both additive manufacturing (AM) and computer numerical control (CNC) machining. HM machines can deposit material in complex shapes that would be difficult or impossible to create by machining while also meeting tolerance or surface finish requirements by integrating a machining capability with the deposition process. Additionally, multi-axis systems can reorient the workpiece such that material can be deposited without the need for support material even if that material would be overhanging past the allowable overhang angle in the original orientation. Reorientation in combination with the ability to remove material also allows multi-axis HM machines to include the substrate partially or fully in the final product, reducing additive feedstock consumption and print times. The process of separating a CAD model into manufacturing sub-volumes and determining the orientation at which each should be deposited or machined is called decomposition. Several decompositions exist for any given CAD model, but not all decompositions are equal. Some decompositions are more favorable than others because they require fewer reorientations, make better use of an integrated substrate, require less post processing, etc. Although multi-axes HM enables efficient manufacturing of complex designs, a well-designed decomposition is necessary to leverage multi-axis HM's capabilities. Currently, CAD models are manually decomposed by HM experts because there are no commercially available software packages that fully automate the decomposition process or the selection of a cost-optimal integrated substrate. The need for such expertise has limited the widespread adoption of HM. To more broadly realize the benefits of HM, decomposition and integrated substrate selection must be automated. Although decomposition algorithms and integrated substrate algorithms have been published previously, this work is the first to introduce a series of algorithms that considers how well a substrate can be integrated into the first manufacturing sub-volume and uses cost-optimization to choose the decomposition and substrate that minimize the cost to fabricate a given CAD model. These algorithms have been implemented in Rhino 3D's coding environment, Grasshopper, to demonstrate their effectiveness.