This study aims to develop a commercialization process for upcycled denim fashion utilizing AI and 3D digital clothing technology, specifically targeting active senior women aged 65 to 80. To this end, three design concepts—Intellectual, Girlish, and Practical—were derived based on senior lifestyles and subsequently visualized using generative AI. Following consultation with five fashion experts, the selected designs were implemented as digital prototypes using CLO software. Post-consumer denim materials were collected and classified into heavyweight and midweight categories to simulate their physical properties within a virtual environment. During this process, factors hindering precise digital twin implementation—such as localized variations in the physical properties inherent in vintage materials and limitations in texture mapping—were empirically analyzed. In particular, the identified technical limitations were utilized as a basis for proactively predicting and managing sewing-related risks during the physical production phase. This research demonstrates both academic and practical significance by establishing a zero-waste methodology that significantly shortens the iterative sampling process while minimizing material waste. By addressing the inefficiencies of traditional manual methods and ensuring a high level of completion prior to production, this study proposes a feasible commercialization model for sustainable fashion.
Lee et al. (Sat,) studied this question.
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