Optimization method to fabrication orientation of parts in fused deposition modeling rapid prototyping

Li, Aijun; Zhang, Zhuohui; Wang, Daoming; Yang, Jinyong

doi:10.1109/mace.2010.5535335

Cited by 25 publications

(15 citation statements)

References 3 publications

(2 reference statements)

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“…In STL format, each triangular surface is expressed by four data items including the three vertices coordinates a j , b j , c j and the normal vector p, while the whole model is a collection of these vectors, as depicted in Figure 1.7. The area of the i th triangular facet [6], A i , calculated from Equation (1.1).…”

Section: Process Planning For Rapid Prototyping and Layered Manufacturingmentioning

confidence: 99%

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Surface roughness estimation for FDM systems

Nourghassemi¹

2021

Preprint

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By selecting the optimal build angle, the surface roughness of rapid prototyped parts can be minimized. The objective of this study is to develop a model for estimation of surface roughness as a function of build angle and other build parameters for parts built by Fusion Deposition Modeling (FDM) machines. For that purpose, principles of the FDM technique, along with other rapid prototyping techniques, are reviewed and various standards for surface roughness measurements are introduced. Different analytical models for the estimation of surface roughness for FDM systems, which were proposed in the literature, are reviewed and reformulated in a standard format for comparison reasons. A new hybrid model is proposed for analytical estimation of the surface roughness based on experimental results and comparison of the models. In addition, Least Square Support Vector Machine (LS-SVM) is applied for an empirical estimation of the surface roughness. Robustness of the LS-SVM model is studied and its performance is compared to the hybrid model. The experimental results confirm better results for the LS-SVM model.

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Section: Process Planning For Rapid Prototyping and Layered Manufacturingmentioning

confidence: 99%

“…[7] also presented a colored map which gives the idea of surface finish at different locations of the part. One of the highly cited and most accepted models for surface roughness estimation for FDM system [15,3,13,6,24] is developed by Pandey et. al.…”

Section: Roughness Model By Campbell Et Al 2002 [7]mentioning

confidence: 99%

Surface roughness estimation for FDM systems

Nourghassemi¹

2021

Preprint

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“…Some researchers have developed methodologies to obtain optimum orientation for best surface finish and reduce build time and support area. Li et al (35) investigated an approach for selecting fabrication orientation for fused deposition rapid prototyping and established a model to optimize the support area, fabrication time, and surface roughness. They used a particle swarm optimization algorithm to obtain fabrication orientation.…”

Section: Part Orientationmentioning

confidence: 99%

Advances in Fused Deposition Modeling

Masood

2014

Comprehensive Materials Processing

138

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“…Cheng et al [4] formulated a multi-objective optimization problem focused on the surface quality and production cost of the parts, obtaining solutions for all types of surfaces, whether with complex geometries or not, or even for curved surfaces. The Particle Swarm Optimization (PSO) algorithm was used in [12] to solve a multi-objective optimization problem in order to get the desired orientations for the support area, build time and surface roughness. A multi-objective optimization approach considering as objective functions the surface roughness and the build time, for different models, was developed by Padhye and Deb in [15].…”

Section: Introductionmentioning

confidence: 99%

A Multi-objective Approach to Solve the Build Orientation Problem in Additive Manufacturing

Matos

Rocha

Costa

et al. 2019

Computational Science and Its Applications – ICCSA 2019

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Additive manufacturing (AM) has been increasingly used in the creation of three-dimensional objects, layer-by-layer, from threedimensional (3D) computer-aided design (CAD) models. The problem of determining the 3D model printing orientation can lead to reduced amount of supporting material, build time, costs associated with the deposited material, labor costs, and other factors. This problem has been formulated and studied as a single-objective optimization problem. More recently, due to the existence and relevance of considering multiple criteria, multi-objective approaches have been developed. In this paper, a multi-objective optimization approach is proposed to solve the part build orientation problem taking into account the support area characteristics and the build time. Therefore, the weighted Tchebycheff scalarization method embedded in the Electromagnetism-like Algorithm will be used to solve the part build orientation bi-objective problem of four 3D CAD models. The preliminary results seem promising when analyzing the Pareto fronts obtained for the 3D CAD models considered. Concluding, the multi-objective approach effectively solved the build orientation problem in AM, finding several compromise solutions.

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Optimization method to fabrication orientation of parts in fused deposition modeling rapid prototyping

Cited by 25 publications

References 3 publications

Surface roughness estimation for FDM systems

Surface roughness estimation for FDM systems

Advances in Fused Deposition Modeling

A Multi-objective Approach to Solve the Build Orientation Problem in Additive Manufacturing

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