기능성 보호복 자동 설계 지원을 위한 착용자 맞춤형 웹 애플리케이션 개발

초록

This study developed a web application to support the user-customized design of functional protective clothing by analyzing wearer characteristics and task conditions. Key design variables—including wearer data, clothing type, exposure to hazardous substances, task intensity, seasonal environment, joint mobility, materials, 2D patterns, and sewing methods—were systematized and stored in a database. The application facilitates non-expert use by enabling users to input conditions step-by-step through an intuitive interface to generate accurate design outputs. By applying logical rule-based filtering, the system also recommends optimized design variables tailored to specific work environments and physical needs. To validate its performance, case scenarios such as chemical protective clothing and military uniforms were tested, with the results demonstrating the system’s effectiveness in providing integrated recommendations on fabrics, 2D patterns, seam types, and virtual fitting images. This platform establishes a foundation for future integration with machine learning, biometric data, and digital simulation tools to support scenario-specific, data-driven clothing solutions.

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