Data-driven Textile Design

Data-Driven Textile Design is a generative textile design methodology that systematically integrates empirical, computational, or sensor-derived data as primary inputs to inform and constrain the design process, distinguishing itself from intuition-based or rule-based approaches through its reliance on quantifiable data to drive pattern generation, material configuration, or structural outcomes.

5

Publications

165

Citations

21

Authors

9

Institutions

Publications per year

2017–2026

3

Authors

21

  1. RH
    Richard Hague

    University of Nottingham, United Kingdom

    1 publications · 24 citations

    1

    h-index

  2. AV
    Armand V. Cardello

    Combat Capabilities Development Command Soldier Center, United States

    1 publications · 45 citations

    1

    h-index

  3. LM
    Les M. Sztandera

    Philadelphia University, United States

    1 publications · 45 citations

    1

    h-index

  4. FR
    Filipe Rodrigues

    Technical University of Denmark, Denmark

    1 publications · 23 citations

    1

    h-index

  5. WV
    Wilhelm van Bronswijk

    Curtin University, Australia

    1 publications · 14 citations

    1

    h-index

1–5 of 21

Venues

  1. Textile Research Journal

    1 publications · 45 citations

    1

    h-index

  2. Rapid Prototyping Journal

    1 publications · 24 citations

    1

    h-index

  3. Forensic Science International

    1 publications · 14 citations

    1

    h-index

  4. 1

    h-index

1–5