A 3D Body Shape Classification Approach for Personalized Menswear Pattern Development: A Case Study
| dc.contributor.author | Huang Zhenzhen | |
| dc.date.accessioned | 2026-05-29T07:07:32Z | |
| dc.date.issued | 2026 | |
| dc.description | Determining correct garment fit remains a significant challenge for manufacturers, particularly in e-commerce, due to variability in human body shapes and technological constraints. Although advancements in 3D technology allow for fit customization, implementing it effectively is complex. This study proposes a 3D body model-based parametric pattern generation method to achieve personalized fit in menswear for mass customization. The research objectives were: (1) To investigate the garment fit factors and the integration of advanced technologies in menswear production processes; (2) To develop a CAD parametric method for generating menswear block and personalized patterns based on 3D body model and body shape classification; and (3) To validate the effectiveness of the proposed pattern generation method in producing accurate personalized fits from 3D body data. A mixed-methods approach was employed: qualitative case studies and interviews showed the integration of 3D technology remains in the experimental phase and has not yet been widely implemented for most apparel firms. Key fit factors included pattern (size system, ease allowance, aesthetics) and technologies (anthropometrics, patternmaking, fitting). Quantitatively, a multi-level male body shape classification method was developed by factor analysis. A parameterized menswear pattern generation method was proposed which employs a pattern-oriented landmark of human feature points to integrate the 3D body model into patternmaking. Finally, virtual fitting comparisons demonstrated that the proposed method improved fit accuracy compared to iv conventional techniques. This research promotes the formulation of a "body-pattern-fit" theory which interprets the relationship between human body size, body type, pattern, and fit, and establishes a methodological framework integrating body data into pattern design and fit evaluation. It provides the industry with a scalable solution for mass customization, reducing returns and improving CAD integration. Future work should explore intelligent and automated 3D pattern-making systems for customization. | |
| dc.identifier.uri | https://scholarhub.unimas.my/handle/123456789/798 | |
| dc.language.iso | English | |
| dc.publisher | Universiti Malaysia Sarawak. | |
| dc.relation.ispartofseries | Faculty of Applied and Creative Arts | |
| dc.subject | Mass customization, | |
| dc.title | A 3D Body Shape Classification Approach for Personalized Menswear Pattern Development: A Case Study | |
| dc.type | PhD |