한국의류학회지 (Journal of the Korean Society of Clothing and Textiles)

  • 제47권4호
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  • Pages.666-683
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  • 2023
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  • 1225-1151(pISSN)
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  • 2234-0793(eISSN)
한국의류학회 (The Korean Society of Clothing and Textiles)
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An AI-based Clothing Design Process Applied to an Industry-university Fashion Design Class

  • Hyosun An (Dept. of Fashion Industry, Ewha Womans University) ;
  • Minjung Park (Dept. of Fashion Industry, Ewha Womans University)
  • 투고 : 2023.04.07
  • 심사 : 2023.08.01
  • 발행 : 2023.08.31
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초록

This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.

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과제정보

The authors sincerely thank the Samsung C&T Fashion Group for their invaluable support and collaboration in developing and conducting the industry-university collaborative class. The authors would like to thank all the students who actively participated in the class, especially Yeeun Kim, Soomin Lee, and Yoonje Cho, for allowing some of their exemplary in-class outcomes in the paper.

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