6. Computational Couture¶
Research & Ideation
Inspiration: Artists and Projects
Computational Couture redefines the way textiles and garments are designed and manufactured by leveraging advanced digital tools such as parametric modeling and 3D printing. This approach allows for the creation of intricate, complex designs that are both customizable and sustainable. The objective of this project is to explore these digital techniques and produce 3D-printed samples that challenge conventional notions of fabric and form.
By integrating artistic inspiration, computational design principles, and cutting-edge fabrication technologies, this project aims to push the boundaries of traditional textile design and demonstrate the potential of a more adaptable, innovative workflow.
Inspiration:
The integration of computational tools in fashion design allows for personalized, interactive, and modular garments. This approach merges technical precision with creative flexibility, enabling the development of complex and adjustable garment structures. Here are key artists and projects influencing computational design in fashion:
Artists and Projects in Computational Couture
1. Iris van Herpen¶
Known for: Avant-garde 3D-printed garments. Insight: Iris van Herpen merges technology with high fashion, using 3D printing and parametric design to create structures resembling natural forms. Her work is a hallmark of computational couture, as it redefines the possibilities of textile structure, shape, and movement. Picture reference: Van Herpen’s 3D-printed couture pieces.
2. Danit Peleg¶
Known for: 3D-printed fashion collections. Insight: Danit Peleg is recognized for her pioneering work in 3D-printed fashion, creating entire collections from home 3D printers. Her designs highlight the potential for sustainable and customizable fashion, made locally and on-demand. Peleg’s work exemplifies the shift towards fully digital fashion production that is accessible to consumers. Picture reference: Peleg’s 3D-printed fashion pieces.
3. Anouk Wipprecht¶
Known for: Interactive, tech-embedded couture. Insight: Wipprecht’s designs, like her “Spider Dress,” use proximity sensors and actuators to respond to the wearer’s environment. This computational approach brings a new level of interactivity, creating fashion that communicates and interacts with the world around it. Picture reference: Wipprecht’s proximity-responsive Spider Dress.
Key Technologies in Computational Couture¶
1.3D Modeling Software¶
- Software: Rhino and Grasshopper are essential for parametric designs, allowing designers to manipulate shapes based on algorithms.
- Impact: These tools provide accuracy and versatility, enabling the creation of modular, scalable garment structures.
- Picture reference: Parametric patterns generated in Rhino.
2.Laser Cutting and 3D Printing¶
- Application: Laser cutting produces precise patterns, while 3D printing enables intricate textures and shapes that would be difficult to achieve with traditional sewing. Impact: These techniques transform flat fabrics into three-dimensional, wearable art.
- Picture reference: Laser-cut garment components.
3.Wearable Microcontrollers¶
- Example: Arduino, Lilypad, and other microcontrollers allow garments to incorporate lighting, sound, or responsive movement based on user interaction.
- Impact: Microcontrollers bring computational couture to life, bridging the gap between fashion and interactive design.
- Picture reference: Microcontroller embedded in garment.
Notable Projects in Computational Couture¶
1.Project Re-FREAM¶
Concept: A collaborative project exploring computational and digital techniques in fashion. Designers experiment with 3D printing, sustainable materials, and computational patterns to create customizable garments. Picture reference: Modular garment patterns from Project Re-FREAM.
2.MODA by Nervous System¶
Concept: A collection of customizable dresses generated using a design algorithm that adapts to individual body measurements. Picture reference: Nervous System’s parametric designs.
Picture credit: Somerville-based Nervous System
3.OpenKnit¶
Concept: An open-source digital knitting machine that allows users to create custom-designed garments from home. Picture reference: Digitally knitted fabric sample.
Picture credit:Phillip Plein
Sketches and Concept Development¶
Initial Sketches¶
Hand-drawn concepts serve as the foundation for the digital designs. These sketches explore:
-Modular, repeating patterns inspired by natural geometries (e.g., honeycomb lattices, spirals). -Dynamic shapes that can stretch, fold, or expand, reflecting versatility in design. Examples: -A triangular mesh that can be 3D-printed as an overlay on fabric. -Circular motifs that interconnect to create a flexible, chainmail-like structure.
Parametric Development¶
The sketches are translated into parametric models using Grasshopper3D. Key parameters like the size, thickness, and connection points of the patterns are defined, allowing for iterative design adjustments.
Grasshopper3D workflow includes:¶
-Generating a base grid or shape (e.g., hexagonal lattice). -Applying algorithms to adjust shape and curvature for flexibility or strength. -Exporting the model for slicing and 3D printing.
Examples of 3D Printing in Fashion To contextualize the project, here are a few noteworthy examples:
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Kinematics Dress by Nervous System: A fully 3D-printed, articulated dress created using parametric algorithms. This design allows for fluid movement despite being made of rigid materials.
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Flexible 3D-Printed Mesh by FDM Printers: Demonstrates how standard 3D printers can create flexible, fabric-like materials using TPU (thermoplastic polyurethane).
- Flexible 3D-Printed Mesh - FDM Printers
Parametric Design Workflow:¶
I explored parametric design using Rhino and Grasshopper to create a visually dynamic and structurally precise facade surface. The process began with defining key inputs such as X-Size and Y-Size to establish the dimensions of the initial rectangular plane, the Count value to control the number of randomly distributed points, and a Curve, which served as the boundary for generating the Voronoi diagram. Using the PlaneSrf component, I created the base plane, while Pop2D distributed random points across the plane. The Voronoi component then generated a Voronoi diagram confined within the provided curve.
Next, I used Explode to extract the individual edges of the Voronoi cells and applied the Pull component to adjust their lengths for a more refined aesthetic. The edges underwent geometric transformation through the Move component, shifting them along a specified vector, while endpoints of these edges were extracted using End. To define spatial boundaries, I calculated the minimum and maximum X-coordinates using Min and Max and generated bounding boxes for each edge using Bnd.
The design progressed to surface generation with the Srf4Pt component, which created surfaces from sets of four points. To enhance the form, I applied SrfMorph, introducing curvature and unique modifications, followed by DeBrep to extract individual faces. Finally, I used Cap to close open edges, resulting in a cohesive and visually compelling output. The final outcome is a modified, closed surface derived from the Voronoi diagram, showcasing the power of parametric design and computational modeling.
The video would actuall take long but here are the close steps in the grasshopper in form of a video formed by screenshots
After finalizing the design in Rhino, I transitioned to Creality Slicer to prepare the model for 3D printing. This slicing step breaks down the design into layers, ensuring that it is suitable for physical production. The sliced model is now ready to be printed, completing the transition from parametric design to a tangible object, ready to be used as part of the parametric facade.
3D Printing and Conclusion:¶
After finalizing the parametric facade design in Rhino and slicing it using Creality Slicer, I proceeded to 3D printing, where the model was physically brought to life. The slicing process ensured that the design could be printed layer by layer, with each section of the model carefully crafted to match the computationally defined structure. The 3D printer then translated the digital design into a physical object, taking 3 hours and 47 minutes to complete the process.
This exploration into parametric design was driven by the desire to push the boundaries of traditional facade design. The integration of randomness, precision, and structural efficiency offers a fresh approach to architectural forms, where aesthetic complexity is paired with functionality. The outcome is a visually dynamic, highly customizable facade that can adapt to various design contexts, opening the door for future applications in architecture and urban planning. The process not only highlighted the potential of computational design but also demonstrated the versatility and power of parametric systems in creating innovative, sustainable structures.