Geometric control of thermoformable knitted textiles using raster images

Computer numerical control (CNC) knitting technology offers great potential in the creation of thermoformable textiles that can be shaped and stiffened in response to heat. Our research explores how CNC knitting can be used to design and fabricate textiles with precisely allocated material and microstructure layouts. These layouts pre-program specific deformation mechanism(s) into the textile that bias it to form an intended geometry, forgoing the need for a mould during the thermoforming process. We fabricate these smart textiles by knitting two thermal-reactive yarns with different extents of shrinkage, in a double layered structure akin to a bilayer strip. We develop a computational design-to-fabrication pipeline that translates raster images into machine-knittable instructions. Referencing multi-material additive manufacturing principles and self-actuating textiles, this paper proposes several design strategies of dithered gradients, tessellated patches and origami creases, to convert input pixel data into a material distribution layout. When paired with our assisted thermoforming process, this layout induces specific deformations of the textile, such as uni-/multi-axial curling, periodic buckling and sharp folding. Our prototypes implement these strategies on the micro-, meso- and macroscale, leading to the design and fabrication of an architectural cladding panel (700 × 535 × 110 mm) and a patterned clutch bag (200 × 420 × 65 mm).