Evidence map›Paper›PMID 33918240›Full record

ArticlePolymers2021

A Design for Additive Manufacturing Strategy for Dimensional and Geometrical Quality Improvement of PolyJet-Manufactured Glossy Cylindrical Features.

Natalia Beltrán, Braulio J Álvarez, David Blanco, Fernando Peña, Pedro Fernández

Abstract read
In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Natalia BeltránIPF Research/ARAMO Group, University of Oviedo, 33203 Gijón, Spain.ORCID 0000-0002-5780-5294
Braulio J ÁlvarezIPF Research/ARAMO Group, University of Oviedo, 33203 Gijón, Spain.ORCID 0000-0001-9042-148X
David BlancoIPF Research/ARAMO Group, University of Oviedo, 33203 Gijón, Spain.ORCID 0000-0001-7867-0010
Fernando PeñaIPF Research/ARAMO Group, University of Oviedo, 33203 Gijón, Spain.ORCID 0000-0002-7379-8362
Pedro FernándezIPF Research/ARAMO Group, University of Oviedo, 33203 Gijón, Spain.ORCID 0000-0001-8329-9391

Funding

ArcelorMittal SV-PA-15-RIS3-4IDEPA SV-PA-15-RIS3-4
6 · The paper itself

Abstract

The dimensional and geometrical quality of additively manufactured parts must be increased to match industrial requirements before they can be incorporated to mass production. Such an objective has a great relevance in the case of features of linear size that are affected by dimensional or geometrical tolerances. This work proposes a design for additive manufacturing strategy that uses the re-parameterization of part design to minimize shape deviations from cylindrical geometries. An analysis of shape deviations in the frequency domain is used to define a re-parameterization strategy, imposing a bi-univocal correspondence between verification parameters and design parameters. Then, the significance of variations in the process and design factors upon part quality is analyzed using design of experiments to determine the appropriate extension for modelling form deviation. Finally, local deviations are mapped for design parameters, and a new part design including local compensations is obtained. This strategy has been evaluated upon glossy surfaces manufactured in a Vero™ material by polymer jetting. The results of the proposed example showed a relevant improvement in dimensional quality, as well as a reduction of geometrical deviations, outperforming the results obtained with a conventional scaling compensation.

Indexed as

design for additive manufacturingfeatures of linear sizematerial jettingquality enhancement

Identifiers

PMID33918240
PMCPMC8038169

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.