인공지능 기반 디자인 플랫폼 사례 연구 - 패션디자인 프로세스 활용성을 중심으로 - (A Case Study of Artificial Intelligence-Based Design Platforms - Focusing on their Utilization in the Fashion Design Process -)

서지정보

· 발행기관 : 한국복식학회
· 수록지 정보 : 복식 / 74권 / 6호 / 69 ~ 93페이지
· 저자명 : LI RUOBING, 양은경

초록

Artificial Intelligence (AI) is revolutionizing the fashion industry, with constant innovation driving the development of new methods for enhancing efficiency and reducing costs in the design process. This study examines the impacts of AI technologies across the five key stages of the fashion design process, emphasizing their core benefits and identifying the main challenges they present. In the data collection and analysis phases of fashion design, AI technologies, such as big data analytics, natural language processing (NLP), computer vision, and sentiment analysis, are employed to assess market trends and consumer behaviors. In terms of concept development, AI tools such as Ablo AI and Designovel automatically generate design drafts and provide data-driven trend forecasts, while platforms such as Khroma facilitate color palette selection. In the design phase, AI facilitates pattern and material creation and makes real-time adjustments through virtual fitting, with tools such as YesPlz and Botika providing high-quality virtual models. In the sample production and evaluation stage, AI enables virtual sample creation and automated quality assessments, enhancing the efficiency and cost-effectiveness of product development. Finally, in the production and execution phase, AI optimizes supply chain management, automates production, and develops customized and stratified marketing strategies. Despite these advancements, certain challenges persist, including data quality and bias issues, limited innovation due to reliance on existing patterns, and difficulties in accurately replicating physical samples virtually. The findings of our research highlight that to enable the optimal integration of AI technologies into the fashion design process, ongoing research and development projects must address these challenges and generate novel technologies that can successfully overcome them.

영어초록

Artificial Intelligence (AI) is revolutionizing the fashion industry, with constant innovation driving the development of new methods for enhancing efficiency and reducing costs in the design process. This study examines the impacts of AI technologies across the five key stages of the fashion design process, emphasizing their core benefits and identifying the main challenges they present. In the data collection and analysis phases of fashion design, AI technologies, such as big data analytics, natural language processing (NLP), computer vision, and sentiment analysis, are employed to assess market trends and consumer behaviors. In terms of concept development, AI tools such as Ablo AI and Designovel automatically generate design drafts and provide data-driven trend forecasts, while platforms such as Khroma facilitate color palette selection. In the design phase, AI facilitates pattern and material creation and makes real-time adjustments through virtual fitting, with tools such as YesPlz and Botika providing high-quality virtual models. In the sample production and evaluation stage, AI enables virtual sample creation and automated quality assessments, enhancing the efficiency and cost-effectiveness of product development. Finally, in the production and execution phase, AI optimizes supply chain management, automates production, and develops customized and stratified marketing strategies. Despite these advancements, certain challenges persist, including data quality and bias issues, limited innovation due to reliance on existing patterns, and difficulties in accurately replicating physical samples virtually. The findings of our research highlight that to enable the optimal integration of AI technologies into the fashion design process, ongoing research and development projects must address these challenges and generate novel technologies that can successfully overcome them.

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