Supportless Fabrication, Experimental, and Numerical Analysis of the Physical Properties for a Thin-Walled Hemisphere
type: CreativeWork
description: 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. 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. It is concluded that planar slicing brings limitations to reduce the number of partitions that can be modified by a constant step over toolpath. On one hand, the partitioning strategy provides an opportunity to fabricate geometries in a supportless fashion by direct energy deposition additive manufacturing, on the other hand, it introduces physical properties challenges such as surface roughness and hardness variations. Process planning, data collection, and experimental/numerical procedures are implemented to investigate the surface roughness variations (Ra measurement) of fabricated domes. Hence, two solutions are developed using Matlab programming. A mount solution uses the magnified pictures of the exposed surface edges of mount samples as input data. The other solution uses a 3D point cloud of the surface. The innovation of the 3D point cloud solution is the distance factor that is applied in the calculations. The results of this solution are compared to the mount solution. Since the input data of the mount solution is more accurate, the results are more reliable than the 3D point cloud method. The Ra variatio…
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. 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. It is concluded that planar slicing brings limitations to reduce the number of partitions that can be modified by a constant step over toolpath. On one hand, the partitioning strategy provides an opportunity to fabricate geometries in a supportless fashion by direct energy deposition additive manufacturing, on the other hand, it introduces physical properties challenges such as surface roughness and hardness variations. Process planning, data collection, and experimental/numerical procedures are implemented to investigate the surface roughness variations (Ra measurement) of fabricated domes. Hence, two solutions are developed using Matlab programming. A mount solution uses the magnified pictures of the exposed surface edges of mount samples as input data. The other solution uses a 3D point cloud of the surface. The innovation of the 3D point cloud solution is the distance factor that is applied in the calculations. The results of this solution are compared to the mount solution. Since the input data of the mount solution is more accurate, the results are more reliable than the 3D point cloud method. The Ra variatio…
author: Kalami, Hamed
language: en_CA
license: http://creativecommons.org/licenses/by-nc-nd/4.0/
date published: 2020-07-29
date modified: 2026-07-27T22:04:56Z
provider: University of Windsor
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Windsor

PropertyValue
property ID: Handle
value: https://hdl.handle.net/20.500.14776/9162