Evidence map›Paper›PMID 39987199›Full record

ArticleScientific reports2025

Optimizing eco-friendly jewelry design through an integrated eco-innovation approach using artificial neural networks.

Anqi Jiang, Meng Huan, Dong-Oun Choi, YunJeong Kang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Anqi JiangCollege of Precious Metals and Gemstone Design, Wonkwang University, Iksan, 54538, Korea. ankia7a7@gmail.com.
Meng HuanSchool of Department of Computer Software Engineering, Wonkwang University, Iksan, 54538, Korea.
Dong-Oun ChoiSchool of Department of Computer Software Engineering, Wonkwang University, Iksan, 54538, Korea.
YunJeong KangSchool of Department of Computer Software Engineering, Wonkwang University, Iksan, 54538, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Achieving sustainable practices in the jewelry industry necessitates the adoption of optimized eco-design approaches. The optimization of eco-friendly jewelry design was investigated in this study through an integrated analysis of materials, digital manufacturing, and predictive modeling. Sustainable techniques were identified, and an artificial neural network (ANN) model was developed to predict environmental impacts based on material properties and design attributes. The applicability of the model was validated, and insights were generated to drive eco-innovation and facilitate the transition towards sustainable practices in the jewelry industry. Key findings demonstrated the superior sustainability of renewable biomaterials, specifically Biomaterials 2-5 derived from lingo-cellulosic sources, compared to conventional materials. Consistently, simpler design configurations outperformed intricate designs. The relationships were effectively captured by the ANN model, providing a reliable evidence-based approach. Quantitative linkages between design attributes and sustainability metrics were established by the study, offering valuable guidance for optimization strategies. Significant results demonstrate that Biomaterials 2-5 exhibit average carbon footprints of 1.1-1.2 kg and water usage of 9-16.5 L, compared to 2.1 kg and 24.5 L for precious metals. Simplified designs exhibit carbon footprints of 0.8 kg and water usage of 11.5 L, whereas intricate designs show footprints of 3.1 kg and water usage of 33 L. These predictions establish renewable biomaterials and streamlined configurations as preferable paradigms for sustainable jewelry. Based on the findings, recommendations include prioritizing the use of Biomaterials 2-5 and streamlined configurations through the implementation of incentives. Transitioning operations towards biomaterial-focused infrastructure and emerging technologies is suggested to further enhance sustainability. Additionally, international cooperation and the development of standards are proposed to address sustainability challenges holistically. The empirical and computational findings of this study establish optimization methodologies that can inspire transformative sustainability practices in the jewelry industry.

Indexed as

Conservation of Natural ResourcesJewelryNeural Networks, ComputerBiocompatible MaterialsBiocompatible MaterialsArtificial neural networksEco-designEco-friendly jewelryEnvironmental impactSustainability

Identifiers

PMID39987199
PMCPMC11846985

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.