Autors: Angelova, R. A.
Title: Digital Twins for a Sustainable Textile Industry: A Critical Analysis of Unexplored Applications and Future Directions
Keywords: cybersecurity, defect simulation, Digital Twins, energy efficiency, ergonomics, personalised production, predictive maintenance, textile industry

Abstract: Digital Twin (DT) models are gaining attention as promising tools for improving efficiency, sustainability, and responsiveness in textile manufacturing. This paper provides a critical review of existing DT applications and outlines seven underexplored areas where such systems could offer tangible benefits. By linking DT models with real-time data, textile producers can optimise energy usage, reduce production errors, enhance machine reliability, and accelerate decision-making processes. Moreover, DTs offer long-term opportunities for smarter waste management, personalised production with lower return rates, and better workforce training. The paper concludes with stakeholder-specific recommendations, such as integrating digital product passports for recyclability, and calls for a cross-disciplinary approach to digital transformation in the sector. These findings offer practitioners a roadmap for adopting DT technologies not only as monitoring tools but as strategic enablers for circularity, agility, and competitiveness.

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Issue

Textiles (Switzerland), vol. 5, 2025, Switzerland, https://doi.org/10.3390/textiles5040049

Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science