Evidence map›Paper›PMID 41303911›Full record

ArticleMaterials (Basel, Switzerland)2025

Optimizing Tensile Strength of Low-Carbon Steel Shafts with Stacked Ring Substrates in WAAM Using Taguchi and Random Forest Regression.

Van-Minh Nguyen, Pham Son Minh, Minh Huan Vo

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 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

3 authors.

Van-Minh NguyenFaculty of Mechanical Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City 71307, Vietnam.ORCID 0009-0009-2454-2764
Pham Son MinhFaculty of Mechanical Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City 71307, Vietnam.ORCID 0000-0002-8236-2202
Minh Huan VoFaculty of Electrical and Electronic Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City 71307, Vietnam.ORCID 0000-0002-9990-9331

Funding

Ho Chi Minh City University of Technology and Education T2024-37
6 · The paper itself

Abstract

Wire Arc Additive Manufacturing (WAAM) enables cost-effective fabrication of complex metallic components but faces challenges in achieving consistent tensile strength for cylindrical parts with intricate internal features (e.g., cooling channels, helical grooves), where conventional machining is often infeasible or prohibitively expensive. This study introduces a novel stacked ring substrate strategy with pre-formed low-carbon steel rings defining complex internal geometries, followed by external WAAM deposition using ER70S-6 wire to overcome these limitations. Five process parameters (welding current: 110-130 A; offset distance: 2.5-3.0 mm; Step Length: rotary to straight; torch speed: 400-500 mm/min; weld thickness: 2.0-3.0 mm) were optimized using a Taguchi L25 orthogonal array (25 runs in triplicate). ANOVA identified Step Length as the dominant factor, with straight paths significantly reducing thermal cycling and improving interlayer bonding, alongside a notable current × speed interaction. Optimal settings achieved tensile strengths of 280-290 MPa, significantly below wrought ER70S-6 benchmarks (400-550 MPa) due to interfacial weaknesses at ring fusion zones and thermal accumulation from stacked cylindrical geometry, a limitation acknowledged in the absence of microstructural or thermal history data. A Random Forest Regressor predicted strength with R

Indexed as

MIG Weldingprocess parameter optimizationrandom forest regressionstep lengthTaguchi L25 orthogonal arraytensile strengthWire Arc Additive Manufacturing (WAAM)

Identifiers

PMID41303911
PMCPMC12654145

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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.