Gregory Dreifus
ABSTRACT
First, we propose a meshing technique using a heuristic circle packing algorithm which generates meshes suitable for 3D printing. Second, we propose a discrete optimization approach to identify the optimal tool path in the mesh. Our approach is motivated by the Miller-Tucker-Zemlin formulation to the traveling salesman problem, and allows us to specify many additional constraints tailored to the AM problem. We present several simulations and also prints on the Oak Ridge National Laboratory's Big Area Additive Manufacturing printer as experimental results.
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Cross Ref
- Philip Bowers. 2009. Introduction to circle packing: the theory of discrete analytic functions {book review}. Bull. Amer. Math. Soc. (N.S.) 46, 3 (2009), 511--525.Google ScholarCross Ref
- Gregory Dreifus, Kyle Goodrick, Scott Giles, Milan Patel, Reed Matthew Foster, Cody Williams, John Lindahl, Brian Post, Alex Roschli, Lonnie Love, and Vlastimil Kunc. 2017. Path optimization along lattices in additive manufacturing. 3D Printing and Additive Manufacturing (2017).Google Scholar
- P. Kulkarni, A. Marsan, and D. Dutta. 2000. A review of process planning techniques in layered manufacturing. Rapid Prototyping Journal 6, 1 (2000), 18--35.Google ScholarCross Ref
- C. E. Miller, A. W. Tucker, and R. A. Zemlin. 1960. Integer programming formulation of traveling salesman problems. Journal of the Association for Computing Machinery 7, 4 (1960), 326--329. Google ScholarDigital Library
- V. Pataki. 2003. Teaching integer programming formulations using the traveling salesman problem. SIAM Rev. 45, 1 (2003), 116--123.Google ScholarDigital Library
Index Terms
- A framework for tool path optimization in fused filament fabrication
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