Design for Additive Manufacturing, to produce assembled products, by SLS

Bâlc, Nicolae; Vilău, Cristian

doi:10.1051/matecconf/201712104002

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…[ 5 ]. Thus, 3D printing is often used to develop medical devices [ 6 ], flexible electronics [ 7 , 8 ], various pieces for automotive or robotics [ 9 ], art objects [ 2 , 3 ], precise replica of archeological objects [ 10 ] etc. Dental implants and porous scaffolds for tissue engineering, with increased surface roughness and improved mechanical performance and biocompatibility, used for bone fixation [ 11 , 12 ] are among the most studied medical devices.…”

Section: Introductionmentioning

confidence: 99%

Recent Advances in 3D Printing of Aliphatic Polyesters

Chiulan

Frone

Brandabur³

et al. 2017

Bioengineering

143

121

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3D printing represents a valuable alternative to traditional processing methods, clearly demonstrated by the promising results obtained in the manufacture of various products, such as scaffolds for regenerative medicine, artificial tissues and organs, electronics, components for the automotive industry, art objects and so on. This revolutionary technique showed unique capabilities for fabricating complex structures, with precisely controlled physical characteristics, facile tunable mechanical properties, biological functionality and easily customizable architecture. In this paper, we provide an overview of the main 3D-printing technologies currently employed in the case of poly (lactic acid) (PLA) and polyhydroxyalkanoates (PHA), two of the most important classes of thermoplastic aliphatic polyesters. Moreover, a short presentation of the main 3D-printing methods is briefly discussed. Both PLA and PHA, in the form of filaments or powder, proved to be suitable for the fabrication of artificial tissue or scaffolds for bone regeneration. The processability of PLA and PHB blends and composites fabricated through different 3D-printing techniques, their final characteristics and targeted applications in bioengineering are thoroughly reviewed.

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Section: Introductionmentioning

confidence: 99%

Recent Advances in 3D Printing of Aliphatic Polyesters

Chiulan

Frone

Brandabur³

et al. 2017

Bioengineering

143

121

View full text Add to dashboard Cite

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“…But still there is a lack of exhaustivity and innovation in the design methodologies to promote sustainability (Lopez Taborda et al , 2021). The objective of DfAM is to create designs that benefit from the advantages of AM, such as increased shape complexity (Gibson et al , 2021), production of multifunctional parts, processing of multiple materials at different locations (Han and Lee, 2020), integration of multiscale features into part geometry (Sossou et al , 2018) and manufacturing of fully assembled parts (Bâlc and Vilǎu, 2017).…”

Section: Introductionmentioning

confidence: 99%

A view similarity-based shape complexity metric to guide part selection for additive manufacturing

Jayapal

Kumaraguru

Varadarajan

2022

RPJ

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Purpose This paper aims to propose a view similarity-based shape complexity metric to guide part selection for additive manufacturing (AM) and advance the goals of design for AM. The metric helps to improve the selection process by objectively screening a large number of parts and identifying the parts most suited for AM and enabling experts to prioritize parts from a smaller set based on relevant subjective/contextual factors. Design/methodology/approach The methodology involves calculating a part’s shape complexity based on the concept of view similarity, that is, the similarity of different views of the outer shape and internal cross-sectional geometry. The combined shape complexity metric (weighted sum of the external shape and internal structure complexity) has been used to rank various three dimensional (3D) models. The metric has been tested for its sensitivity to various input parameters and thresholds are suggested for effective results. The proposed metric’s applicability for part selection has also been investigated and compared with the existing metric-based part selection. Findings The proposed shape complexity metric can distinguish the parts of different shapes, sizes and parts with minor design variations. The method is also efficient regarding the amount of data and computation required to facilitate the part selection. The proposed method can detect differences in the mass properties of a 3D model without evaluating the modified parameters. The proposed metric is effective in initial screening of a large number of parts in new product development and for redesign using AM. Research limitations/implications The proposed metric is sensitive to input parameters, such as the number of viewpoints, design orientation, image resolution and different lattice structures. To address this issue, this study suggests thresholds for each input parameter for optimum results. Originality/value This paper evaluates shape complexity using view similarity to rank parts for prototyping or redesigning with AM.

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