IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2197-d1045906.html
   My bibliography  Save this article

Dynamic Fit Optimization and Effect Evaluation of a Female Wetsuit Based on Virtual Technology

Author

Listed:
  • Xinzhou Wu

    (School of Fashion, Wuhan Textile University, Wuhan 430073, China
    Wuhan Textile and Clothing Digital Engineering Technology Research Center, Wuhan 430073, China)

  • Zhe Cheng

    (School of Fashion, Wuhan Textile University, Wuhan 430073, China
    Wuhan Textile and Clothing Digital Engineering Technology Research Center, Wuhan 430073, China)

  • Victor E. Kuzmichev

    (School of Fashion, Wuhan Textile University, Wuhan 430073, China
    Institute of Textile Industry and Fashion, Ivanovo State Polytechnic University, 153000 Ivanovo, Russia)

Abstract

At present, the traditional mode of research and development for mass-produced wetsuits usually requires repeated sample making and try-on evaluation, and performance cannot be predicted, monitored and evaluated in real time; this can lead to problems including low material utilization and production efficiency. In this study, real human body static and dynamic measurements, material properties and structure data are applied through 3D software to build an accurate virtual model, and new wetsuits are designed through simulation, optimization and evaluation. The static and dynamic fitting performance above and underwater is comprehensively evaluated in virtual and real environments, and it is proved that the virtual development mode can accurately and effectively guide the development and evaluation of wetsuits, and can meet personalized comfort and functional requirements today. This simulation evaluation method avoids repeated sample preparation, some unnecessary waste of materials and environmental pollution, and improves manufacturing efficiency.

Suggested Citation

  • Xinzhou Wu & Zhe Cheng & Victor E. Kuzmichev, 2023. "Dynamic Fit Optimization and Effect Evaluation of a Female Wetsuit Based on Virtual Technology," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2197-:d:1045906
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2197/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2197/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fei Tao & Qinglin Qi, 2019. "Make more digital twins," Nature, Nature, vol. 573(7775), pages 490-491, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jian-Guo Duan & Tian-Yu Ma & Qing-Lei Zhang & Zhen Liu & Ji-Yun Qin, 2023. "Design and application of digital twin system for the blade-rotor test rig," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 753-769, February.
    2. Sajjad Rahmanzadeh & Mir Saman Pishvaee & Kannan Govindan, 2023. "Emergence of open supply chain management: the role of open innovation in the future smart industry using digital twin network," Annals of Operations Research, Springer, vol. 329(1), pages 979-1007, October.
    3. Chengjun Li & Liguo Yao & Yao Lu & Songsong Zhang & Taihua Zhang, 2025. "DTL-GNN: Digital Twin Lightweight Method Based on Graph Neural Network," Future Internet, MDPI, vol. 17(2), pages 1-24, February.
    4. F. H. Abanda & N. Jian & S. Adukpo & V. V. Tuhaise & M. B. Manjia, 2025. "Digital twin for product versus project lifecycles’ development in manufacturing and construction industries," Journal of Intelligent Manufacturing, Springer, vol. 36(2), pages 801-831, February.
    5. Evangelos Katsamakas, 2024. "Business models for the simulation hypothesis," Papers 2404.08991, arXiv.org.
    6. Dapai Shi & Jingyuan Zhao & Chika Eze & Zhenghong Wang & Junbin Wang & Yubo Lian & Andrew F. Burke, 2023. "Cloud-Based Artificial Intelligence Framework for Battery Management System," Energies, MDPI, vol. 16(11), pages 1-21, May.
    7. Xueru Zhang & Dennis K. J. Lin & Lin Wang, 2023. "Digital Triplet: A Sequential Methodology for Digital Twin Learning," Mathematics, MDPI, vol. 11(12), pages 1-16, June.
    8. Bai, Fan & Quan, Hong-Bing & Yin, Ren-Jie & Zhang, Zhuo & Jin, Shu-Qi & He, Pu & Mu, Yu-Tong & Gong, Xiao-Ming & Tao, Wen-Quan, 2022. "Three-dimensional multi-field digital twin technology for proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 324(C).
    9. Muhammad Ali Musarat & Alishba Sadiq & Wesam Salah Alaloul & Mohamed Mubarak Abdul Wahab, 2022. "A Systematic Review on Enhancement in Quality of Life through Digitalization in the Construction Industry," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    10. Kerstens, Andrea & Langley, David J., 2025. "An innovation intermediary’s role in enhancing absorptive capacity for cross-industry digital innovation: Introducing an awareness capability and new intermediary practices," Journal of Business Research, Elsevier, vol. 196(C).
    11. Pin Wu & Lulu Ji & Wenyan Yuan & Zhitao Liu & Tiantian Tang, 2023. "A Digital Twin Framework Embedded with POD and Neural Network for Flow Field Monitoring of Push-Plate Kiln," Future Internet, MDPI, vol. 15(2), pages 1-20, January.
    12. Jieyin Lyu & Shouqin Zhou & Jingang Liu & Bingchun Jiang, 2023. "Intelligent-Technology-Empowered Active Emergency Command Strategy for Urban Hazardous Chemical Disaster Management," Sustainability, MDPI, vol. 15(19), pages 1-28, September.
    13. Ruixue Zhang & Huate Zhu & Qinglin Chang & Qirong Mao, 2025. "A Comprehensive Review of Digital Twins Technology in Agriculture," Agriculture, MDPI, vol. 15(9), pages 1-25, April.
    14. Milad Elyasi & Simon Thevenin & Audrey Cerqueus, 2025. "Use of AI in assembly line design and worker and equipment management: review and future directions," Flexible Services and Manufacturing Journal, Springer, vol. 37(2), pages 367-408, June.
    15. Majidi Nezhad, Meysam & Neshat, Mehdi & Sylaios, Georgios & Astiaso Garcia, Davide, 2024. "Marine energy digitalization digital twin's approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    16. Sheng-Wen Zhou & Shun-Sheng Guo & Wen-Xiang Xu & Bai-Gang Du & Jun-Yong Liang & Lei Wang & Yi-Bing Li, 2024. "Digital Twin-Based Pump Station Dynamic Scheduling for Energy-Saving Optimization in Water Supply System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(8), pages 2773-2789, June.
    17. Yongzhi Wang & Shaoming Liao & Zhiqun Gong & Fei Deng & Shiyou Yin, 2024. "Enhancing Construction Management Digital Twins Through Process Mining of Progress Logs," Sustainability, MDPI, vol. 16(22), pages 1-29, November.
    18. Zhang, Anshan & Wang, Feiliang & Li, Huanyu & Pang, Bo & Yang, Jian, 2024. "Carbon emissions accounting and estimation of carbon reduction potential in the operation phase of residential areas based on digital twin," Applied Energy, Elsevier, vol. 376(PB).
    19. Zio, Enrico & Miqueles, Leonardo, 2024. "Digital twins in safety analysis, risk assessment and emergency management," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    20. Jielin Chen & Shuang Li & Hanwei Teng & Xiaolong Leng & Changping Li & Rendi Kurniawan & Tae Jo Ko, 2025. "Digital twin-driven real-time suppression of delamination damage in CFRP drilling," Journal of Intelligent Manufacturing, Springer, vol. 36(2), pages 1459-1476, February.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2197-:d:1045906. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.