Evidence map›Paper›PMID 38894250›Full record

ArticleSensors (Basel, Switzerland)2024

On-Machine LTS Integration for Layer-Wise Surface Quality Characterization in MEX/P.

Alejandro Fernández, Pablo Zapico, David Blanco, Fernando Peña, Natalia Beltrán, Sabino Mateos

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

6 authors.

Alejandro FernándezDepartment of Construction and Manufacturing Engineering, University of Oviedo, 33203 Gijón, Asturias, Spain.ORCID 0000-0003-3795-3238
Pablo ZapicoDepartment of Construction and Manufacturing Engineering, University of Oviedo, 33203 Gijón, Asturias, Spain.ORCID 0000-0001-8055-8650
David BlancoDepartment of Construction and Manufacturing Engineering, University of Oviedo, 33203 Gijón, Asturias, Spain.ORCID 0000-0001-7867-0010
Fernando PeñaDepartment of Construction and Manufacturing Engineering, University of Oviedo, 33203 Gijón, Asturias, Spain.ORCID 0000-0002-7379-8362
Natalia BeltránDepartment of Construction and Manufacturing Engineering, University of Oviedo, 33203 Gijón, Asturias, Spain.ORCID 0000-0002-5780-5294
Sabino MateosDepartment of Construction and Manufacturing Engineering, University of Oviedo, 33203 Gijón, Asturias, Spain.ORCID 0000-0002-6542-3931

Funding

Spanish Ministry of Science, Innovation and Universities; FEDER DPI2017-83068-P
6 · The paper itself

Abstract

Material Extrusion (MEX) currently stands as the most widespread Additive Manufacturing (AM) process, but part quality deficiencies remain a barrier to its generalized industrial adoption. Quality control in MEX is a complex task as extrusion performance impacts the consistency of mechanical properties and the surface finish, dimensional accuracy, and geometric precision of manufactured parts. Recognizing the need for early-stage process monitoring, this study explores the potential of integrating Laser Triangulation Sensors (LTS) into MEX/P manufacturing equipment for layer-wise 3D inspections. Using a double-bridge architecture, an LTS-based sub-micrometric inspection system operates independently from the manufacturing process, enabling comprehensive digitization and autonomous reconstruction of the target layer's topography. Surface texture is then computed using standardized indicators and a new approach that provides insight into layer quality uniformity. A case study evaluating two alternative extruder head designs demonstrates the efficacy of this integrated approach for layer quality characterization. Implementing a generalized layer-wise procedure based on this integration can significantly mitigate quality issues in MEX manufacturing and optimize process parameter configurations for enhanced performance.

Indexed as

additive manufacturinglaser triangulationlayer-wise scanningMEX/P

Identifiers

PMID38894250
PMCPMC11174827

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.