Collaborative Research: FW-HTF-P: Reducing Finished-Product Waste through Augmented Design Intelligence

在美国，每人每年生产或进口的服装足以购买约90件新衣服--总计约280亿件--其中绝大多数很少或从未使用过。在这个项目中，研究团队试图建立工具来帮助设计师生产更有可能使用的服装，以便将未售出的商品、退货和未充分利用的购买降至最低。为了做到这一点，研究团队将调查设计师和消费者在决策时使用的信息，并确定计算机智能可以在哪些领域为设计师提供支持：例如，让设计师更多地获得有关消费者偏好的信息，或者通过推荐数百万潜在设计中最有可能穿的设计。该项目的总体目标是减少消费者生产但从未经常使用的服装数量，为服装行业的工作描绘一个更可持续的未来。该项目发展奖将绘制问题空间并开发初步工具，以支持未来一个整合了广泛的行业利益相关者的更大规模的项目。将对服装设计师目前的设计做法进行深入的定性调查，以确定决策过程并使其正式化，以确定决策支持工具可以产生变革影响的领域。这些领域的信息需求将被正式确定，并将与专业设计师合作开发早期原型决策支持工具。将收集消费者偏好和产品属性的数据集，并将其用于制定评估决策支持工具影响的方法。这些工具的经济影响将被建模，以帮助理解和预测设计实践的重大变化对供应链中其他工人的影响。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.