Title:
Voxel-based tool sequence optimization for 5-axis machining using high performance computing
Voxel-based tool sequence optimization for 5-axis machining using high performance computing
Author(s)
Ameur, Amir
Advisor(s)
Kurfess, Thomas R.
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Abstract
This thesis presents an approach for tool sequence optimization in the case of 5-axis machining. Most of the reported work suggests tooling optimization methods involving parametric surfaces and CPU-enabled algorithms. In the current work, a novel voxel-based approach is presented. The main advantage of this 3D-representation is the ability to parallelize different operations executed on single voxels and run them on parallel platforms such as GPU cores. This work is realized through Sculptrprint, a voxelized GPGPU-enabled CAM software, and introduces 3 different algorithms to optimize the tool sequence selection. Each of the formulated strategies is based on the optimization of one or two machining objectives and has a GPU-only implementation.
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Date Issued
2017-08-15
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Resource Type
Text
Resource Subtype
Thesis