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This is a Quantitative Study study.

September 23, 2025Applied SciencesOpen Access

Machine Learning-Based Data Quality Assessment for the Textile and Clothing Digital Product Passport

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Authors

ECEstrela Ferreira CruzPolytechnic Institute of Viana do Castelo PSPedro Silva SSS Serra

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Implication

This analysis evaluates data quality assessment using machine learning for the digital product passport, highlighting challenges in transparency for textile businesses.

Key Points

Machine learning algorithms enhance the validation of data quality for the digital product passport.
The study identifies four machine learning solutions that cater to various datasets from textile companies.
Data integration from diverse companies is crucial for the effective implementation of the digital product passport.
Sustainability is supported by improved transparency in the textile and clothing value chain through better data management.

Cite This Study

Cruz et al. (2025) studied this question.

synapsesocial.com/papers/68d4724f31b076d99fa6ad9c https://doi.org/10.3390/app151810259

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Implication

This analysis evaluates data quality assessment using machine learning for the digital product passport, highlighting challenges in transparency for textile businesses.

Machine Learning-Based Data Quality Assessment for the Textile and Clothing Digital Product Passport

Discussion

Member takes

Implication

Key Points

Cite This Study

Machine Learning-Based Data Quality Assessment for the Textile and Clothing Digital Product Passport

Discussion

Member takes

Implication

Key Points

Cite This Study

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