Evidence map›Paper›PMID 41470985›Full record

ArticlePolymers2025

Extruder Path Analysis in Fused Deposition Modeling Using Thermal Imaging.

Juan M Cañero-Nieto, Rafael J Campo-Campo, Idanis B Díaz-Bolaño, José F Solano-Martos, Diego Vergara, Edwan A Ariza-Echeverri, Crispulo E Deluque-Toro

Abstract read
In one paragraph

Article in Polymers, 2025. 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

7 authors.

Juan M Cañero-NietoDept. Civil, Materials and Manufacturing Engineering, Escuela de Ingenierías Industriales, Universidad de Málaga, Andalucía Tech, Campus de Teatinos, 29071 Málaga, Spain.ORCID 0000-0003-0893-9891
Rafael J Campo-CampoGrupo de Nuevos Materiales y Didáctica de las Ciencias, Facultad de Ingeniería, Universidad del Magdalena, Santa Marta 470004, Colombia.
Idanis B Díaz-BolañoGrupo de Investigación y Desarrollo en Sistemas y Computación, Facultad de Ingeniería, Universidad del Magdalena, Santa Marta 470004, Colombia.ORCID 0009-0003-1349-6113
José F Solano-MartosDept. Civil, Materials and Manufacturing Engineering, Escuela de Ingenierías Industriales, Universidad de Málaga, Andalucía Tech, Campus de Teatinos, 29071 Málaga, Spain.ORCID 0000-0002-1141-8977
Diego VergaraTechnology, Instruction and Design in Engineering and Education Research Group (TiDEE.rg), Catholic University of Avila, C/Canteros s/n, 05005 Ávila, Spain.ORCID 0000-0003-3710-4818
Edwan A Ariza-EcheverriGrupo de Nuevos Materiales y Didáctica de las Ciencias, Facultad de Ingeniería, Universidad del Magdalena, Santa Marta 470004, Colombia.ORCID 0000-0002-2442-7362
Crispulo E Deluque-ToroGrupo de Nuevos Materiales y Didáctica de las Ciencias, Facultad de Ingeniería, Universidad del Magdalena, Santa Marta 470004, Colombia.ORCID 0000-0001-7792-3506

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fused deposition modeling (FDM) is one of the most widely adopted additive manufacturing (AM) technologies due to its accessibility and versatility; however, ensuring process reliability and product quality remains a significant challenge. This work introduces a novel methodology to evaluate the fidelity of programmed extruder head trajectories and speeds against those executed during the printing process. The approach integrates infrared thermography and image processing. A type-V ASTM D638-14 polylactic acid (PLA) specimen was fabricated using 16 layers, and its G-code data were systematically compared with kinematic variables extracted from long-wave infrared (LWIR) thermal images. The results demonstrate that the approach enables the detection of deviations in nozzle movement, providing valuable insights into layer deposition accuracy and serving as an early indicator for potential defect formation. This thermal image-based monitoring can serve as a non-invasive tool for in situ quality control (QC) in FDM, supporting process optimization and improved reliability of AM polymer components. These findings contribute to the advancement of smart sensing strategies for integration into industrial additive manufacturing workflows.

Indexed as

additive manufacturing (AM)extruder path analysisG-codeinfrared thermography (IRT)in situ quality controlpolylactic acid (PLA)process monitoring

Identifiers

PMID41470985
PMCPMC12736861

What OpenQuestion holds

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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.