Combined optimization of part topology, support structure layout and build orientation for additive manufacturing

The advent of Additive Manufacturing (AM) process has greatly broadened the machining methods. Compared to conventional manufacturing methods, the process planning for AM is totally different. It should avoid process-induced defects such as warpage of overhang features. Process planning for AM should also generate necessary support structure not only to support the overhang structure but also to minimize thermal warpage and residual stress. In order to do so, a general process planning for AM is put forward in this paper. Given a specific part, the first step is the determination of build orientation. The choice of build orientation is one of the critical factors in AM since the build time, the material consumption, the removal of support structure, the deformation within final parts, the mechanical performance, and the surface roughness are all related to the build orientation. This paper utilizes the genetic algorithm to optimize the build orientation by considering the minimum volume of the support structure and the minimum strain energy of a part under specific working conditions. First, a general and feasible process planning for AM is proposed. Then detailed process planning for the optimization of build orientation is developed. The volume of support structure and strain energy are considered independently and corresponding optimal build orientations are obtained through genetic algorithm. A single weighted aggregate optimization function is then constructed to optimize the volume of support structure and strain energy simultaneously. Finally, a bracket is used to verify the feasibility of the proposed method.

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Multi-material thermomechanical topology optimization with applications to additive manufacturing: Design of main composite part and its support structure

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2019.112812 ◽

2020 ◽

Vol 363 ◽

pp. 112812 ◽

Cited By ~ 5

Author(s):

Oliver Giraldo-Londoño ◽

Lucia Mirabella ◽

Livio Dalloro ◽

Glaucio H. Paulino

Keyword(s):

Topology Optimization ◽

Additive Manufacturing ◽

Composite Part ◽

Support Structure ◽

Manufacturing Design

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Bayesian Inference-Based Decision of Fatigue Life Model for Metal Additive Manufacturing Considering Effects of Build Orientation and Post-Processing

International Journal of Fatigue ◽

10.1016/j.ijfatigue.2021.106535 ◽

2021 ◽

pp. 106535

Author(s):

Jaehyeok Doh ◽

Nandhini Raju ◽

Nagarajan Raghavan ◽

David W. Rosen ◽

Samyeon Kim

Keyword(s):

Fatigue Life ◽

Additive Manufacturing ◽

Bayesian Inference ◽

Post Processing ◽

Metal Additive Manufacturing ◽

Build Orientation ◽

Life Model ◽

Metal Additive

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A statistical method for build orientation determination in additive manufacturing

Rapid Prototyping Journal ◽

10.1108/rpj-04-2018-0102 ◽

2019 ◽

Vol 25 (1) ◽

pp. 187-207 ◽

Cited By ~ 11

Author(s):

Yicha Zhang ◽

Ramy Harik ◽

Georges Fadel ◽

Alain Bernard

Keyword(s):

Additive Manufacturing ◽

Statistical Method ◽

Supervised Machine Learning ◽

Surface Model ◽

Generic Level ◽

Content Type ◽

Build Orientation ◽

Cad Models ◽

Feature Based ◽

Orientation Determination

Purpose For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and costly computation. To deal with these issues, this paper aims to introduce a new statistical method to develop fast automatic decision support tools for additive manufacturing build orientation determination. Design/methodology/approach The proposed method applies a non-supervised machine learning method, K-Means Clustering with Davies–Bouldin Criterion cluster measuring, to rapidly decompose a surface model into facet clusters and efficiently generate a set of meaningful alternative build orientations. To evaluate alternative build orientations at a generic level, a statistical approach is defined. Findings A group of illustrative examples and comparative case studies are presented in the paper for method validation. The proposed method can help production engineers solve decision problems related to identifying an optimal build orientation for complex and freeform CAD models, especially models from the medical and aerospace application domains with much efficiency. Originality/value The proposed method avoids the limitations of traditional feature-based methods and pure computation-based methods. It provides engineers a new efficient decision-making tool to rapidly determine the optimal build orientation for complex and freeform CAD models.

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Additive manufacturing of 316L stainless-steel structures using fused filament fabrication technology: mechanical and geometric properties

Rapid Prototyping Journal ◽

10.1108/rpj-06-2020-0120 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Miguel Ángel Caminero ◽

Ana Romero ◽

Jesús Miguel Chacón ◽

Pedro José Núñez ◽

Eustaquio García-Plaza ◽

...

Keyword(s):

Stainless Steel ◽

Additive Manufacturing ◽

Austenitic Stainless Steel ◽

Material Properties ◽

Steel Structures ◽

Fused Filament Fabrication ◽

Geometric Properties ◽

Content Type ◽

Build Orientation ◽

Manufacturing Alternatives

Purpose Fused filament fabrication (FFF) technique using metal filled filaments in combination with debinding and sintering steps can be a cost-effective alternative for laser-based powder bed fusion processes. The mechanical behaviour of FFF-metal materials is highly dependent on the processing parameters, filament quality and adjusted post-processing steps. In addition, the microstructural material properties and geometric characteristics are inherent to the manufacturing process. The purpose of this study is to characterize the mechanical and geometric performance of three-dimensional (3-D) printed FFF 316 L metal components manufactured by a low-cost desktop 3-D printer. The debinding and sintering processes are carried out using the BASF catalytic debinding process in combination with the BASF 316LX Ultrafuse filament. Special attention is paid on the effects of build orientation and printing strategy of the FFF-based technology on the tensile and geometric performance of the 3-D printed 316 L metal specimens. Design/methodology/approach This study uses a toolset of experimental analysis techniques [metallography and scanning electron microcope (SEM)] to characterize the effect of microstructure and defects on the material properties under tensile testing. Shrinkage and the resulting porosity of the 3-D printed 316 L stainless steel sintered samples are also analysed. The deformation behaviour is investigated for three different build orientations. The tensile test curves are further correlated with the damage surface using SEM images and metallographic sections to present grain deformation during the loading progress. Mechanical properties are directly compared to other works in the field and similar additive manufacturing (AM) and Metal Injection Moulding (MIM) manufacturing alternatives from the literature. Findings It has been shown that the effect of build orientation was of particular significance on the mechanical and geometric performance of FFF-metal 3-D printed samples. In particular, Flat and On-edge samples showed an average increase in tensile performance of 21.7% for the tensile strength, 65.1% for the tensile stiffness and 118.3% for maximum elongation at fracture compared to the Upright samples. Furthermore, it has been able to manufacture near-dense 316 L austenitic stainless steel components using FFF. These properties are comparable to those obtained by other metal conventional processes such as MIM process. Originality/value 316L austenitic stainless steel components using FFF technology with a porosity lower than 2% were successfully manufactured. The presented study provides more information regarding the dependence of the mechanical, microstructural and geometric properties of FFF 316 L components on the build orientation and printing strategy.

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Automated Geometric Correction System for Additive Manufacturing Considering Build Orientation

Journal of Mechanical Design ◽

10.1115/1.4051353 ◽

2021 ◽

pp. 1-30

Author(s):

Seyedeh Elaheh Ghiasian ◽

Kemper Lewis

Keyword(s):

Additive Manufacturing ◽

Optimization Model ◽

Experimental Validation ◽

Minimal Amount ◽

Feature Size ◽

Build Orientation ◽

Computational Performance ◽

The Difference ◽

Processing Effort ◽

Correction System

Abstract One of the current challenges for the additive manufacturing (AM) industry lies in providing component designs compatible with the AM manufacturability and constraints without compromising the component structural functionalities. To address this challenge, we present an automated correction system that provides geometrically feasible designs for additive processes by applying locally effective modifications while avoiding substantial changes in the current designs. Considering a minimum printable feature size from the process parameters, this system identifies the problematic features in an infeasible part's design using a holistic geometric assessment algorithm. Based on the obtained manufacturability feedback, the system then corrects the detected problematic regions using a set of appropriate redesign solutions through an automated procedure. In addition, to reduce the difference between the current and modified part geometries, a novel optimization model for build orientation is presented. Using this model, one can identify appropriate orientations for obtaining a feasible design with a minimal amount of corrections while also reducing the post-processing effort by minimizing the area of contact with the support structure. The functionalities of the presented correction system and the optimization model are illustrated using a number of case studies with varying geometries. The computational performance of the system and an experimental validation are also presented to demonstrate the effectiveness of the implemented detection and modification approaches.

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