A Rule-Based Parametric Workflow for Tessellation-Based 3D-Printed Textile Textures: A Haptic-Relevant Design Exploration

Authors

  • Yixin Liu Kingston School of Art, Kingston University, London KT1 2EE, United Kingdom Author
  • Mingjing Lin Kingston School of Art, Kingston University, London KT1 2EE, United Kingdom Author
  • Sylvia Tzvetanova Yung Kingston School of Art, Kingston University, London KT1 2EE, United Kingdom Author

DOI:

https://doi.org/10.64509/jdi.11.52

Keywords:

Parametric Design, Rule-based Parametric Workffow, Computational Design, Digital Fabrication, 3D-Printed Textile Textures, Tessellation-based Patterns

Abstract

Quadrilateral-based continuous textile patterns are well suited to large-scale fabrication as rhythmic surface effects can be produced through repetition, translation and rotation. This paper presents a rule-based parametric design workflow for three-dimensional (3D)-printed textile textures based on tessellation patterns with continuous geometric properties that was developed through shape grammar principles and implemented in the Grasshopper visual programming environment. During testing, the workflow demonstrated how a square-based geometric primitive—defined here as a planar base unit with edge-to-edge continuity suitable for tessellation construction—can be systematically transformed into tessellated textile textures through parametric rules and form, forming a reproducible digital-to-physical pipeline from algorithmic generation to physical realisation. The square primitive was employed as an exemplar case due to its geometric clarity, while the underlying shape grammar rules and parametric operations were not restricted to a specific geometry and could have been extended to alternative planar primitives. The study focused on the integration of geometric rule definition, parametric variation and fabrication constraints within textile-integrated fused deposition modelling (FDM). Physical validation was therefore limited to printability, material feasibility and structural coherence using thermoplastic polyurethane (TPU) rather than empirical evaluation of tactile perception. Within this scope, haptic qualities were addressed as design-relevant dimensions embedded in geometric variation and fabrication parameters. Key parametric variables, which were defined through a set of explicitly structured geometric and fabrication parameters, provided a reproducible basis for future physical and perceptual evaluation. The contribution of this work lies in establishing a fabrication-aware, rule-based parametric workflow that bridges computational design logic and digital textile fabrication.

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Author Biographies

  • Yixin Liu, Kingston School of Art, Kingston University, London KT1 2EE, United Kingdom

    Yixin Liu is currently a third-year PhD student at Kingston University, specialising in fashion technology and haptic design within textiles. Her research explores the emotional impact of material-based tactile interactions, aiming to enhance affective textile design through practice-based integration of technologies. She holds an MA in Garment Pattern and Technology from the University of the Arts London. Prior to her doctoral studies, she served as a lecturer at the Beijing Institute of Fashion Technology, where she accumulated three years of experience teaching undergraduate courses in textile design.

  • Mingjing Lin, Kingston School of Art, Kingston University, London KT1 2EE, United Kingdom

    Dr. Mingjing Lin is a senior lecturer in Textile Science and STEM Practice at London College of Fashion. She earned a PhD in Textile Design from the Royal College of Art in 2020, where her practice-based research focused on body-oriented parametric design and a new framework for 3D-printed fashion and textiles, called Parametric Thinking 2.0. Dr. Lin has led the 3D Textile training sessions for the EuropeAid Metamorphosis Project. (https://www.arts.ac.uk/knowledge-exchange/our-funded-projects/metamorphosis) Her work has been showcased internationally since 2011, including at the V&A Museum, London Fashion Week, Disseny de Barcelona, and the National Museum of China. Using a S.T.E.A.M. approach, she continually explores digital fashion, wearable technology, and smart textiles, pushing the boundaries of art, design, and technology.

  • Sylvia Tzvetanova Yung, Kingston School of Art, Kingston University, London KT1 2EE, United Kingdom

    Dr Sylvia Tzvetanova Yung is an Associate Professor at the Kingston School of Art, Kingston University. She conducts research for the benefit of human well-being using sustainable practices combined with technology and AI. She explores design and emotion and how this should impact on the design directions. Dr Sylvia Tzvetanova Yung received Innovation Seedcorn Funding for the project Emotional Well Being Tracker, which involves collaboration with medical practitioners to build an AI system. Prior to joining Kingston, she worked internationally both in academia and industry as an interaction designer and as an educator. She was the editor of numerous major international design research conferences and workshops - including DesignEd Asia, part of the Business of Design week Hong Kong (BODW), Design & Emotion conference 2008 and IASDR 2007.

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JDI62

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Published

2026-01-31

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Section

Articles

How to Cite

Liu, Y., Lin, M., & Tzvetanova Yung, S. (2026). A Rule-Based Parametric Workflow for Tessellation-Based 3D-Printed Textile Textures: A Haptic-Relevant Design Exploration. Journal of Design Intelligence , 1(1), 27-38. https://doi.org/10.64509/jdi.11.52