Evidence map›Paper›PMID 42198151›Full record

ArticlePolymers2026

Comparative Analysis of AWJM Performance in FFF-Printed PLA and PLA-CF: Influence of Process Parameters and Cutting Regions.

Pedro F Mayuet Ares, Lucía Rodríguez-Parada, Sergio de la Rosa, Moises Batista

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

4 authors.

Pedro F Mayuet AresMechanical Engineering and Industrial Design Department, School of Engineering, University of Cadiz, Avda. de la Universidad de Cádiz, 10, E11519 Puerto Real, Spain.ORCID 0000-0001-5751-676X
Lucía Rodríguez-ParadaMechanical Engineering and Industrial Design Department, School of Engineering, University of Cadiz, Avda. de la Universidad de Cádiz, 10, E11519 Puerto Real, Spain.ORCID 0000-0001-9294-7557
Sergio de la RosaMechanical Engineering and Industrial Design Department, School of Engineering, University of Cadiz, Avda. de la Universidad de Cádiz, 10, E11519 Puerto Real, Spain.ORCID 0000-0001-7374-7410
Moises BatistaMechanical Engineering and Industrial Design Department, School of Engineering, University of Cadiz, Avda. de la Universidad de Cádiz, 10, E11519 Puerto Real, Spain.ORCID 0000-0001-8385-966X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Additive manufacturing by Fused Filament Fabrication (FFF) enables the fabrication of complex polymer components, although limitations in surface quality and dimensional accuracy often require post-processing. Abrasive water jet machining (AWJM) is a non-thermal technique suitable for improving surface integrity in polymers and composites without inducing thermal damage. This study investigates the AWJM performance on FFF-printed polylactic acid (PLA) and carbon-fiber-reinforced PLA (PLA-CF), focusing on the influence of water pressure (WP), traverse feed rate (TFR), and abrasive mass flow rate (AMFR). A full factorial design was implemented, and surface integrity was evaluated through surface roughness (Ra) and kerf taper (T), considering their variation across characteristic cutting regions: initial damage region (IDR), smooth cutting region (SCR), and rough cutting region (RCR). Results show that WP and TFR are the dominant parameters, while AMFR has a limited effect within the studied range. The SCR exhibits the lowest roughness, whereas the RCR shows significant degradation due to energy loss. Both materials present similar behavior, with only minor improvements in PLA-CF. ANOVA confirms that process parameters have a stronger influence than material type, providing useful criteria for AWJM optimization in FFF polymers.

Indexed as

abrasive water jet machiningfused filament fabricationpolylactic acidprocess parameterssurface integrity

Identifiers

PMID42198151
PMCPMC13211052

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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.