ArticleScientific reports2026
Elucidating formability limits in warm incremental sheet forming of AZ61 magnesium alloy using integrated grey relational and data-driven analysis.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The growing demand for lightweight structural components in the automotive and aerospace sectors has intensified interest in magnesium alloys; however, their limited formability at room temperature continues to restrict widespread industrial adoption. In this study, the formability and surface quality of AZ61 magnesium alloy during warm incremental sheet forming (ISF) are systematically investigated. A straight-groove forming test was conducted using a Taguchi L27 experimental design to evaluate the effects of key process parameters. To simultaneously optimize formability and surface roughness, Grey Relational Analysis (GRA) was employed. Analysis of Variance (ANOVA) of the GRA results revealed that step depth was the most influential parameter, contributing 70.12% to the total variance, followed by spindle speed with a contribution of 12.97%, while tool diameter and feed rate exhibited comparatively minor effects. The optimal parameter combination, 8 mm tool diameter, 700 rpm spindle speed, 0.3 mm step depth, and 500 mm/min feed rate, resulted in enhanced formability and improved surface quality. Forming Limit Diagram (FLD) analysis confirmed an expansion of the safe deformation zone under optimized conditions. Scanning Electron Microscopy (SEM) observations indicated a predominantly ductile fracture mode characterized by deep dimples and fibrous tearing. Furthermore, a Random Forest-based machine learning model corroborated the ANOVA findings, providing additional validation and trend confirmation for the identified parameter influences. The integrated experimental and data-driven framework presented in this work supports the development of intelligent and optimized warm ISF processes for magnesium alloys.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.