A systematic review of voxelization method in additive manufacturing

Abstract

Additive manufacturing (AM) is becoming an important alternative to traditional processes. AM technology shows several advantages in literature, and its use increases in aerospace, automotive and biomedicine. Time reduction in design-to-manufacturing cycle, customization, capability to generate complex shapes in one piece and ability to imitate low-weight bio-inspired shapes are the strength of designs based on AM. Due to its potentials, major progresses were done in AM, thanks to technology evolution and increased computational power. With regard to AM, voxelization can be defined as part’s discretization in hexahedral elements, as done with pixels in 2D image. Voxels are used to speed-up geometry and algebraic manipulation thanks to their inherent advantages. This paper analyses advantages and criticalities of AM and voxel manipulation through a systematic literature review methodology. The analyses are based upon the filtering of a huge amount of publications available in literature up to obtaining the most significant 25 studies published in the last 5 years. The study’s main result is the technology gap’s identification, i.e. where AM and voxelization still need improvements, thus providing the reader with suggestions about possible further studies. Computer elaboration power and voxel discretization algorithms are suggested being key issues in AM’s further development.

An overview of additive manufacturing technologies for musical wind instruments

“…A systematic literature search was performed [18]. The initial search contained variations or combinations of the following terms and keywords: three-dimensional printing; additive manufacturing.…”

Search for the Optimal Build Direction in Additive Manufacturing Technologies: A Review

“…The main limitation of the methods based on the voxelization of tessellated models is the high computational cost [65], that is not compatible with any optimization method requiring many iterations. For this reason , Di Angelo et al [40] introduced an innovative algorithm without voxelization (Figure 9), which is particularly suitable for an optimization task, due to its accuracy and efficiency.…”

An Optimization Workflow in Design for Additive Manufacturing

“…On the other hand, to fully exploit the AM technologies' potential, many needs in different sub-fields were highlighted [1,[3][4][5][6][7][8], as summarized in Figure 1. For example, a highly skilled workforce is required, file formats for exchanging the data related to the AM workflow need enhancements [8,9], and design methods and tools for complex structures, multi-material parts, and functionally graded materials need to be improved [10,11]. The concerns over the structural integrity of these complex parts require static and dynamic mechanical characterization [12,13]; also, experimental tests help to mechanically characterize the materials, skilled workforce is required, file formats for exchanging the data related to the AM workflow need enhancements [8,9], and design methods and tools for complex structures, multi-material parts, and functionally graded materials need to be improved [10,11].…”

“…For example, a highly skilled workforce is required, file formats for exchanging the data related to the AM workflow need enhancements [8,9], and design methods and tools for complex structures, multi-material parts, and functionally graded materials need to be improved [10,11]. The concerns over the structural integrity of these complex parts require static and dynamic mechanical characterization [12,13]; also, experimental tests help to mechanically characterize the materials, skilled workforce is required, file formats for exchanging the data related to the AM workflow need enhancements [8,9], and design methods and tools for complex structures, multi-material parts, and functionally graded materials need to be improved [10,11]. The concerns over the structural integrity of these complex parts require static and dynamic mechanical characterization [12,13]; also, experimental tests help to mechanically characterize the materials, and the obtained information is used in numerical simulations to predict the different mechanical behavior between the products obtained through additive manufacturing and the ones obtained by traditional techniques of material subtraction [14,15].…”