Estimating Yarn Length for Machine-Knitted Structures

• Gabrielle Ohlson
• Angelica Bonilla Fominaya
• Kavya Puthuveetil
• Jenny Wang
• Emily Amspoker
• Jim McCann

Abstract

We show that a linear model is sufficient to accurately estimate the quantity of yarn that goes into a knitted item produced on an automated knitting machine. Knitted fabrics are complex structures, yet their diverse properties arise from the arrangement of a small number of discrete, additive operations. One can estimate the masses of each of these basic yarn additions using linear regression and, in turn, use these masses to estimate the overall quantity (and local distribution) of yarn within any knitted fabric. Our proposed linear model achieves low error on a range of fabrics and generalizes to different yarns and stitch sizes. This paves the way for applications where having a known yarn distribution is important for accuracy (e.g., simulation) or cost estimation (e.g., design).

Links

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Citation

Gabrielle Ohlson, Angelica M. Bonilla Fominaya, Kavya Puthuveetil, Jenny Wang, Emily Amspoker, and James McCann. 2023. Estimating Yarn Length for Machine-Knitted Structures. In Proceedings of the 8th ACM Symposium on Computational Fabrication (SCF ‘23). Article 3. https://doi.org/10.1145/3623263.3623355

@inproceedings{ohlson:2023:yarn-length,
author = {Ohlson, Gabrielle and Bonilla Fominaya, Angelica M. and Puthuveetil, Kavya and Wang, Jenny and Amspoker, Emily and McCann, James},
title = {Estimating Yarn Length for Machine-Knitted Structures},
year = {2023},
isbn = {9798400703195},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3623263.3623355},
doi = {10.1145/3623263.3623355},
booktitle = {Proceedings of the 8th ACM Symposium on Computational Fabrication},
articleno = {3},
numpages = {9},
location = {New York City, NY, USA},
series = {SCF '23}
}