Abstract
The relationship between visual appearance and structure and technical properties of a knitted fabric is subtle and complex. This is an area that has been traditionally problematic within the knitting sector, understanding between technologists and designers is hindered which limits the possibility of dialogues from which design innovation can emerge. Recently there has been interest from the Human-Computer Interaction (HCI) community to narrow the gap between product design and knitwear. The goal of this article is to show the potential of predictive software design tools for fashion designers who are developing personalized advanced functionalities in textile products. The main research question explored in this article is: “How can designers benefit from intelligent design software for the manufacturing of personalized advanced functionalities in textile products?”. In particular we explored how to design interactions and interfaces that use intelligent predictive algorithms through the analysis of a case study, in which several predictive algorithms were compared in the practice of textile designers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
ten Bhömer, M., Canova, R., de Laat, E.: Body inspired design for knitted body-protection wearables. In: Proceedings of the 2018 ACM Conference Companion Publication on Designing Interactive Systems, pp. 135–139. ACM, New York (2018)
ten Bhömer, M., Jeon, E., Kuusk, K.: Vibe-ing: designing a smart textile care tool for the treatment of osteoporosis. In: Chen, L.L., et al. (eds.) Proceedings of the 8th International Conference on Design and Semantics of Form and Movement, pp. 192–195. Koninklijke Philips Design (2013)
Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)
Black, S.: Innovative knitwear design utilising seamless and unconventional construction, London, UK (2002)
Eckert, C.: The communication bottleneck in knitwear design: analysis and computing solutions. Comput. Support. Coop. Work 10(1), 29–74 (2001)
Hsu, C.H., Wang, M.J.J.: Using decision tree-based data mining to establish a sizing system for the manufacture of garments. Int. J. Adv. Manuf. Technol. 26(5), 669–674 (2005)
Jaouachi, B., Khedher, F.: Evaluation of sewed thread consumption of jean trousers using neural network and regression methods. Fibres Text. East. Eur. 23, 91–96 (2015)
Karmon, A., Sterman, Y., Shaked, T., Sheffer, E., Nir, S.: KNITIT: a computational tool for design, simulation, and fabrication of multiple structured knits. In: Proceedings of the 2nd ACM Symposium on Computational Fabrication, pp. 4:1–4:10. ACM, New York (2018)
Kuhn, M., Johnson, K.: Applied Predictive Modeling. Springer, New York (2013). https://doi.org/10.1007/978-1-4614-6849-3
Lau, F., Yu, W.: Seamless knitting of intimate apparel. In: Yu, W. (ed.) Advances in Women’s Intimate Apparel Technology, pp. 55–68. Woodhead Publishing (2016)
Matković, V.M.P.: The power of fashion: the influence of knitting design on the development of knitting technology. Textile 8(2), 122–146 (2010)
Matusiak, M.: Application of artificial neural networks to predict the air permeability of woven fabrics. Fibres Text. East. Eur. 23, 41–48 (2015)
McCann, J., et al.: A compiler for 3D machine knitting. ACM Trans. Graph. 35(4), 49:1–49:11 (2016)
Narayanan, V., Albaugh, L., Hodgins, J., Coros, S., Mccann, J.: Automatic machine knitting of 3D meshes. ACM Trans. Graph. 37(3), 35:1–35:15 (2018)
Ogulata, S.N., Sahin, C., Ogulata, R.T., Balci, O.: The prediction of elongation and recovery of woven bi-stretch fabric using artificial neural network and linear regression models. Fibres Text. East. Eur. 14(2), 9–46 (2006)
Power, E.J.: Advanced knitting technologies for high-performance apparel. In: McLoughlin, J., Sabir, T. (eds.) High-Performance Apparel, pp. 113–127. Woodhead Publishing (2018)
Sayer, K., Wilson, J., Challis, S.: Seamless knitwear - the design skills gap. Des. J. 9(2), 39–51 (2006)
Spencer, D.J.: Knitting Technology: A Comprehensive Handbook and Practical Guide, 3rd edn. Woodhead Publishing, Sawston (2001)
Yildirim, P., Birant, D., Alpyildiz, T.: Data mining and machine learning in textile industry. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 8(1), e1228 (2018)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (NSFC, Grant No. 51750110497). Many thanks for the generous support of Santoni Shanghai, Studio Eva x Carola, and the support from Yuanjin Liu and Yifan Zhang.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
ten Bhömer, M., Liang, HN., Yu, D. (2019). Machine Learning Enhanced User Interfaces for Designing Advanced Knitwear. In: Stephanidis, C. (eds) HCI International 2019 - Posters. HCII 2019. Communications in Computer and Information Science, vol 1033. Springer, Cham. https://doi.org/10.1007/978-3-030-23528-4_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-23528-4_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23527-7
Online ISBN: 978-3-030-23528-4
eBook Packages: Computer ScienceComputer Science (R0)