CM/Collaborative Research: Simulation-based Software Tools for Automated Knitting

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A growing fraction of textile products, particularly clothing, are made on sophisticated automated knitting machines that can produce complete products in a single step, with full control over variation in shape, appearance, and mechanical properties across the surface of the fabric. These machines promise to democratize the design of garments and other knitted products: any design that can be written down as a knitting machine program can be made in any quantity as easily as a mass-produced product, and every instance can be different, with variations in size, fit, and function. Ironically, very few people can actually design custom knitted garments for automated manufacture on these machines, because developing new patterns is a trial-and-error process requiring esoteric knowledge and access to the production equipment. This project aims to change this situation by developing simulation technology that enables web-based interactive design tools that accurately predict the end result, eliminating trial-and-error and letting users directly manufacture their designs with confidence of good results the first time. An emphasis on interactive web-based design tools will enable a practical pathway for expanding access and real-world usage. The project's technical aims include: (1) Achieve predictive simulation of yarn mechanics by extending prior work on yarn-level cloth modeling to provide a calibrated match to experimental data. (2) Develop multi-scale simulation models that provide real-time feedback for interactive design tasks involving design-related edits to knit structures. (3) Build simulation-based design tools that anyone can use to easily design and simulate their own custom knitted products in the same way one can now 3D print mechanical parts. (4) Investigate high-level optimization-based design tools that enable "smart" edits without resorting to low-level stitch specifications. We will evaluate our simulation tools using a sequence of user studies that measure the effectiveness of the tools to improve users' ability to match design targets.