CAREER: Developing Computational Tools to Revitalize the U.S. Textile Manufacturing Workforce

职业：开发计算工具以振兴美国纺织制造劳动力

• 批准号: 2048022
• 负责人: Fatma Baytar
• 金额: $ 53.78万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048022&HistoricalAwards=false
• 关键词: CAREER; Developing; Computational; Tools; Revitalize

The loss of U.S. apparel production jobs overseas and a subsequent decline in manufacturing infrastructure after the 1980s was highlighted during the COVID-19 pandemic, when demand for domestically produced personal protective equipment could not be met. In order to address this deficit, the U.S. textile industry requires the physical and human resources to update, upskill, and accelerate manufacturing. At the core of this transformation are 2D/3D digital technologies, which enable instant product iterations and quickly move garments from development into production. Currently, digital competence is low for many in the U.S. textile manufacturing workforce, which has traditionally preferred manual techniques and questioned the accuracy of digital technologies, thus limiting rates of adoption. In education, there is a lack of knowledge about how to integrate 3D digital technologies into the curriculum, which has made it challenging to develop a tech-savvy future workforce and provide training to the existing workforce.To address these gaps, the overarching goal of this CAREER project is to accelerate digitalization in manufacturing by: (1) creating a novel computational tool to replace in-person fit sessions during new product development, and facilitate rapid decision-making when using 2D/3D digital technologies, and (2) designing effective training modules for the current and future workforce to strengthen their core knowledge and growth. Tools and research findings from this project will advance scholarly knowledge and make a contribution across the fields such as textiles, learning sciences, computer science, and human-computer interaction. In addition, the methods proposed in this research will pave the way to create new jobs in U.S. manufacturing industries at the intersection of design, ergonomics, and technology, which will significantly benefit from the computational tool and cyber learning approaches developed in this project. A major educational component of the research focuses on leveraging the digital skills of the technologically savvy cohort, and includes organizing workshops for educators, designing curricular materials, providing research involvement and mentoring of undergraduate and graduate students, and outreach to 4-H and K-12 students.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.

20世纪80年代后，美国服装生产岗位在海外流失，制造业基础设施随之下降，这在2019冠状病毒病大流行期间突显出来，当时国内生产的个人防护设备的需求无法得到满足。为了解决这一赤字，美国纺织业需要物质和人力资源来更新，提升技能和加速制造。这种转变的核心是2D/3D数字技术，它可以实现即时产品迭代，并快速将服装从开发转移到生产。目前，美国纺织制造业的许多劳动力的数字能力很低，他们传统上更喜欢手工技术，并质疑数字技术的准确性，从而限制了采用率。在教育领域，人们对如何将3D数字技术整合到课程中缺乏了解，这使得培养精通技术的未来劳动力和为现有劳动力提供培训变得非常具有挑战性。为了解决这些差距，该CAREER项目的总体目标是通过以下方式加速制造业的数字化：（1）创建一种新颖的计算工具，以在新产品开发期间取代面对面的适配会话，并在使用2D/3D数字技术时促进快速决策，及（2）为现时及未来的员工设计有效的培训模式，以加强他们的核心知识及增长。该项目的工具和研究成果将促进学术知识的发展，并在纺织品，学习科学，计算机科学和人机交互等领域做出贡献。此外，本研究中提出的方法将为在设计，人体工程学和技术交叉点的美国制造业创造新的就业机会铺平道路，这将大大受益于本项目中开发的计算工具和网络学习方法。该研究的一个主要教育组成部分侧重于利用精通技术的群体的数字技能，包括为教育工作者组织研讨会，设计课程材料，提供研究参与和指导本科生和研究生，和4-H和K的联系该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准。

项目成果

The Importance of Deciphering Tacit Knowledge in Apparel Product Development for Explainable AI: Proposed steps for increasing digitalization in the apparel industry

• DOI: 10.1145/3549737.3549806
• 发表时间: 2022-09
• 期刊: Proceedings of the 12th Hellenic Conference on Artificial Intelligence
• 作者: Fatma Baytar;Yoo-sun Yang;Mona Maher

A Conceptual Approach for Using VR and Digital Simulations to Train Students in Fit Assessment and Correction Skills

使用 VR 和数字模拟培训学生合身评估和纠正技能的概念方法

• DOI: 10.31274/itaa.15814
• 发表时间: 2022
• 期刊: 2022 Annual Conference of ITAA (International Textile and Apparel Association
• 作者: Galada, Aditi;Baytar, Fatma
• 通讯作者: Baytar, Fatma

An Improved ‘Team Mental Model’ as an Assessment Tool for Group Decision-Making During Fit Sessions

改进的“团队心理模型”作为健身会议期间团体决策的评估工具

• DOI: 10.31274/itaa.16043
• 发表时间: 2022
• 期刊: 2022 Annual Conference of ITAA (International Textile and Apparel Association
• 作者: Yang, Yoon;Baytar, Fatma
• 通讯作者: Baytar, Fatma