Topology optimization and additive manufacturing: Comparison of conception methods using industrial codes

Saadlaoui, Yassine; Milan, Jean-Louis; Rossi, Jérémy; Chabrand, Patrick

doi:10.1016/j.jmsy.2017.03.006

Cited by 109 publications

(53 citation statements)

References 27 publications

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“…Especially in the case of metal components, the interest of the industry is growing exponentially [1] because AM allows the production of fully dense near-net-shaped parts with complex structures made with excellent materials [2]. In fact, the main advantage of AM over conventional subtractive or formative methods is clearly illustrated by the greater product functionality that can be achieved by proper exploitation of the freedom in design [3,4].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Density, Roughness, and Accuracy of the Atomic Diffusion Additive Manufacturing (ADAM) Process for Metal Parts

Galati

Minetola

2019

Materials

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Atomic Diffusion Additive Manufacturing (ADAM) is a recent layer-wise process patented by Markforged for metals based on material extrusion. ADAM can be classified as an indirect additive manufacturing process in which a filament of metal powder encased in a plastic binder is used. After the fabrication of a green part, the plastic binder is removed by the post-treatments of washing and sintering (frittage). The aim of this work is to provide a preliminary characterisation of the ADAM process using Markforged Metal X, the unique system currently available on the market. Particularly, the density of printed 17-4 PH material is investigated, varying the layer thickness and the sample size. The dimensional accuracy of the ADAM process is evaluated using the ISO IT grades of a reference artefact. Due to the deposition strategy, the final density of the material results in being strongly dependent on the layer thickness and the size of the sample. The density of the material is low if compared to the material processed by powder bed AM processes. The superficial roughness is strongly dependent upon the layer thickness, but higher than that of other metal additive manufacturing processes because of the use of raw material in the filament form. The accuracy of the process achieves the IT13 grade that is comparable to that of traditional processes for the production of semi-finished metal parts.

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Section: Introductionmentioning

confidence: 99%

Analysis of Density, Roughness, and Accuracy of the Atomic Diffusion Additive Manufacturing (ADAM) Process for Metal Parts

Galati

Minetola

2019

Materials

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“…Most CAD software typically offers packages for topology optimization based on environmental structure and/or thermal loads, whereby, the software will determine a geometry that safely withstands the prescribed environment while simultaneously minimizing a design metric such as mass or operating temperature capability [121]. These techniques, while successful in designing complex geometries, are mainly based on preliminary design and final function, and not the AM processing parameters.…”

Section: Emerging Metal-am Applications For Modeling and Simulationmentioning

confidence: 99%

Invited review article: Metal-additive manufacturing—Modeling strategies for application-optimized designs

Bandyopadhyay

Traxel

2018

Additive Manufacturing

128

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Next generation, additively-manufactured metallic parts will be designed with application-optimized geometry, composition, and functionality. Manufacturers and researchers have investigated various techniques for increasing the reliability of the metal-AM process to create these components, however, understanding and manipulating the complex phenomena that occurs within the printed component during processing remains a formidable challenge—limiting the use of these unique design capabilities. Among various approaches, thermomechanical modeling has emerged as a technique for increasing the reliability of metal-AM processes, however, most literature is specialized and challenging to interpret for users unfamiliar with numerical modeling techniques. This review article highlights fundamental modeling strategies, considerations, and results, as well as validation techniques using experimental data. A discussion of emerging research areas where simulation will enhance the metal-AM optimization process is presented, as well as a potential modeling workflow for process optimization. This review is envisioned to provide an essential framework on modeling techniques to supplement the experimental optimization process.

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“…These benefits include reduction in manufacturing costs through lower material usage and shorter print times, and potential reduction in the component's distortions and residual stresses. Several tools and techniques have been widely adapted for lightweighting in AM design, including the use of topology, shape and size optimization, and inclusion of lattice structures [2,[5][6][7]. An example of how topology optimization can be used in component design is described in Figure 1, where a hydraulic valve block has been redesigned for Nurmi Cylinders Oy [8].…”

Section: Materials Minimizationmentioning

confidence: 99%

Design approaches for additive manufactured components, with a focus on selective laser melting

Komi¹,

Kokkonen²

2017

RakMek

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Summary. Additive manufacturing (AM) of metal components is characterized by the joining of material particles or feedstock to make parts described by 3D model data in typically a layer by layer fashion. These modern and constantly improving manufacturing techniques inherently allow far more geometric freedom than traditional "subtractive" manufacturing processes, and thus necessitate novel approaches to component design. Careful utilization of this geometric freedom can be translated into products characterized by improved functionality and performance, simplified assemblies, are customizable, and/or lightweight. This paper provides a brief overview design approaches, manufacturing limitations, and available tools for successful design of additive manufactured components, with special attention paid to the selective laser melting (SLM) approach.

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Topology optimization and additive manufacturing: Comparison of conception methods using industrial codes

Cited by 109 publications

References 27 publications

Analysis of Density, Roughness, and Accuracy of the Atomic Diffusion Additive Manufacturing (ADAM) Process for Metal Parts

Analysis of Density, Roughness, and Accuracy of the Atomic Diffusion Additive Manufacturing (ADAM) Process for Metal Parts

Invited review article: Metal-additive manufacturing—Modeling strategies for application-optimized designs

Design approaches for additive manufactured components, with a focus on selective laser melting

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