Digital Twins for a Sustainable Textile Industry: A Critical Analysis of Unexplored Applications and Future Directions
Radostina A. Angelova
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.