设计预测工具的个性化功能在针织性能磨损

Q1 Arts and Humanities Temes de Disseny Pub Date : 2019-07-25 DOI:10.46467/tdd35.2019.42-75
Martijn Ten Bhömer, Hai-Ning Liang, Difeng Yu, Yuanjin Liu, Yifan Zhang, Eva De Laat, Carola Leegwater
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引用次数: 1

摘要

先进的纺织制造技术的发展——比如3D塑形针织品机械——允许生产几乎定型的服装,这几乎不需要进一步的生产步骤来定型服装。此外,先进的针织技术与新材料相结合,可以在“一针一针”的水平上将服装的局部功能集成在一起。通过使用数据收集、机器学习和模拟等技术,有可能增强先进针织制造的设计工具。这种方法反映了工业4.0的潜力,因为设计、产品开发和制造正在紧密联系在一起。然而,目前关于这些新技术和工具如何对创意设计过程产生影响的知识仍然有限。本文提出的案例研究探讨了预测软件设计工具的潜力,为正在开发纺织品个性化高级功能的时装设计师提供帮助。本文探讨的主要研究问题是:“设计师如何从智能设计软件中受益,以制造纺织产品的高级个性化功能?”在这个更大的研究问题中,探讨了三个子研究问题:(1)在针织服装的个性化过程中可以考虑什么样的高级功能?(2)在服装设计过程中,如何设计使用智能预测算法来激发创造力的交互和界面?(3)预测软件将如何影响其他利益相关者的制造过程和生产步骤?这些问题是通过研究设计案例研究的分析来调查的,在这个案例研究中,几种预测算法被比较并在一个用户界面中实现,这将有助于针织服装设计师在高性能跑步袜的开发过程中。
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Designing Predictive Tools for Personalized Functionalities in Knitted Performance Wear
Developments of advanced textile manufacturing techniques—such as 3D body-forming knitwear machinery—allows the production of almost finalized garments, which require little to no further production steps to finalize the garment. Moreover, advanced knitting technology in combination with new materials enables the integration of localized functionalities within a garment on a “stitch by stitch level.” There is potential in enhancing the design tools for advanced knitting manufacturing through the use of technologies such as data gathering, machine learning, and simulation. This approach reflects the potential of Industry 4.0, as design, product development, and manufacturing are moving closer together. However, there is still limited knowledge at present about how these new technologies and tools can have an impact on the creative design process. The case study presented in this paper explores 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 advanced personalized functionalities in textile products?”. Within this larger research question three sub-research questions are explored: (1) What kind of advanced functionalities can be considered for the personalization process of knitwear? (2) How to design interactions and interfaces that use intelligent predictive algorithms to stimulate creativity during the fashion design process? (3) How will predictive software impact the manufacturing process for other stakeholders and production steps? These questions are investigated through the analysis of a Research Through Design case study, in which several predictive algorithms were compared and implemented in a user interface that would aid knitwear designers during the development process of high-performance running tights.
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来源期刊
CiteScore
1.00
自引率
0.00%
发文量
8
审稿时长
30 weeks
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