Evidence map›Paper›PMID 42195466›Full record

ArticleMicromachines2026

Response Surface Modeling and Parameter Optimization of Microgroove Depth in Water-Jet-Guided Laser Machining of L605 Alloy.

Shimin Yang, Yugang Zhao, Qilong Fan, Li Guo, Zhi Qi, Kai Xing, Yusheng Zhang

Abstract read
In one paragraph

Article in Micromachines, 2026. 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
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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

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.

Shimin YangSchool of Mechanical Engineering, Shandong University of Technology, No. 266 Xincun West Road, Zibo 255049, China.
Yugang ZhaoSchool of Mechanical Engineering, Shandong University of Technology, No. 266 Xincun West Road, Zibo 255049, China.
Qilong FanSchool of Mechanical Engineering, Shandong University of Technology, No. 266 Xincun West Road, Zibo 255049, China.
Li GuoSchool of Mechanical Engineering, Shandong University of Technology, No. 266 Xincun West Road, Zibo 255049, China.
Zhi QiSchool of Mechanical Engineering, Shandong University of Technology, No. 266 Xincun West Road, Zibo 255049, China.
Kai XingSchool of Mechanical Engineering, Shandong University of Technology, No. 266 Xincun West Road, Zibo 255049, China.
Yusheng ZhangSchool of Mechanical Engineering, Shandong University of Technology, No. 266 Xincun West Road, Zibo 255049, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

L605 cobalt-based superalloy is a typical difficult-to-machine material because of its high strength, pronounced work hardening, and low thermal conductivity. To improve the microgroove machining performance of this alloy, a self-developed water-jet-guided laser (WJGL) system equipped with a multi-focus lens was employed, and single-factor experiments together with a Box-Behnken response surface design were conducted to investigate the effects of laser power, pulse frequency, water pressure, and feed speed on microgroove depth. The results showed that microgroove depth increased with laser power, decreased with pulse frequency and feed speed, and first increased and then decreased with water pressure. Analysis of variance demonstrated that the developed quadratic regression model was significant and fit the data well. A recommended parameter combination of 274.9 W laser power, 3334.9 Hz pulse frequency, 1.636 MPa water pressure, and 0.107 mm/s feed speed corresponded to a predicted microgroove depth of 621.2 μm. Validation experiments yielded an average microgroove depth of 600.2 μm, with a relative error of 3.4%, indicating that the model can be used for microgroove depth prediction and parameter selection in WJGL machining of L605 alloy and may provide guidance for future multi-objective optimization considering both machining quality and efficiency.

Indexed as

L605 alloymicrogroove depthresponse surface methodologywater-jet-guided laser

Identifiers

PMID42195466
PMCPMC13209472

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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.