Collaborative Research: FW-HTF-P: Reducing Finished-Product Waste through Augmented Design Intelligence
Collaborative Research: FW-HTF-P: Reducing Finished-Product Waste through Augmented Design Intelligence
批准号:
2222905
负责人:
Sheng Lu
金额:
$1.9万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-10-01 至 2024-03-31
中文摘要
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英文摘要
In the US, enough clothing is manufactured or imported for every person to purchase around 90 new garments per year – about 28 billion in total -- the vast majority of which are rarely or never used. In this project, the research team seeks to build tools to help designers produce clothing that is more likely to be used in order to minimize unsold merchandise, returns, and underused purchases. To do this, the research team will investigate the information that is used by designers and consumers in making decisions and identify areas in which computer intelligence can support designers: for instance, by giving designers more access to information about consumers’ preferences, or by recommending which among millions of potential designs might be ones most likely to be worn. The overall goal of the project is to reduce the amount of clothing that is produced but never ends up in regular use by a consumer, charting a more sustainable future for work in the clothing industry.This project development award will map the problem space and develop preliminary tools to support a future larger-scale project that integrates a broad array of industry stakeholders. An in-depth qualitative investigation of clothing designers’ current design practices will be used to identify and formalize decision-making processes in order to identify areas in which decision-support tools could have a transformative impact. Information needs in these areas will be formalized, and early prototype decision-support tools will be developed in collaboration with professional designers. A dataset of consumer preferences and product attributes will be collected and used to develop methods of assessing the impact of decision-support tools. The economic impacts of these tools will be modeled to help understand and predict effects of major changes to design practice on other workers in the supply chain.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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