FW-HTF-RL: Collaborative Research: The Future of Remanufacturing: Human-Robot Collaboration for Disassembly of End-of-Use Products
FW-HTF-RL: Collaborative Research: The Future of Remanufacturing: Human-Robot Collaboration for Disassembly of End-of-Use Products
批准号:
2026276
负责人:
Sara Behdad
金额:
$151.42万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30
中文摘要
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英文摘要
This Future of Work at the Human Technology Frontier (FW-HTF) project will advance effective human-robot collaboration (HRC) to reduce electronics remanufacturing costs and improve operator safety, while considering the highly complex unstructured nature of the remanufacturing environment. Scarcity of resources, environmental regulations, and potential profits from salvaging valuable materials and components have motivated consideration of end-of-use product recovery and remanufacturing. However there are significant challenges related to the labor-intensive nature of disassembly, which is an integral part of critical remanufacturing operations such as reuse, repair, maintenance, and recycling. This project focuses on robot-assisted disassembly to increase productivity, while enhancing job satisfaction and ensuring worker safety. Today, disassembly is still a predominantly labor-intensive process that requires direct contact with many elements that are potentially harmful to human health. The research will advance fundamental understanding of the way humans and robots distribute tasks, cooperate, and interact in a safe and complementary manner. Among the expected benefits of the research results are improved quality of life for remanufacturing workers, increased recycling and reduced waste for used electronic materials, the creation of new manufacturing jobs, reduced dependency on foreign sources of strategic materials, and increased stocks of domestically harvested rare earth elements. The multidisciplinary research crosses the boundaries between robotics, sustainable design, human factors, data science, and labor economics, by the joint efforts between the University at Buffalo (UB) and the University of Florida (UF). The research will positively impact engineering education and workforce development through educational and outreach activities such as workshops for K12 students, course development at both institutions, timely training of graduate students, and a set of workshops for industry and academic audiences. The project is focused on advancing an integrated framework that utilizes the capabilities of both humans and robots in a safe, complementary, and interactive manner, towards designing an economically viable disassembly system for the remanufacturing industry. The research team will perform fundamental studies on collaborative disassembly systems by implementing five interdependent research tasks within the contexts of Future Technology, Future Worker, and Future Work: (1) work environment monitoring with human motion prediction, (2) planning, learning, and control for collaborative robots, (3) disassembly sequence planning under uncertainty and exploring HRC-inspired design guidelines, (4) human-robotics system integration, and (5) modeling and prediction of economic impacts of HRC in remanufacturing environments. Specific knowledge gaps are addressed by mutual interactions among product design guidelines, HRC, occupational safety standards, and remanufacturing labor market. The convergent research approach will allow iteratively adjusted and enhanced collaborative disassembly systems to be implemented in future remanufacturing factories.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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Optimization-Based Disassembly Sequence Planning Under Uncertainty for Human-Robot Collaboration
不确定性下基于优化的人机协作拆卸顺序规划
DOI:
10.1115/msec2022-85383
发表时间:
2022
期刊:
The ASME Manufacturing Science and Engineering Conference (MSEC
影响因子:
--
作者:
[Liao, Hao-yu, Chen, Yuhao, Hu, Boyi, Behdad, Sara]
通讯作者:
Behdad, Sara
The Effect of Different Occupational Background Noises on Voice Recognition Accuracy
不同职业背景噪声对语音识别准确度的影响
DOI:
10.1115/1.4053521
发表时间:
2022
期刊:
Journal of computing and information science in engineering
影响因子:
3.1
作者:
[Song, Li, Ozkan Yerebakan, Mustafa, Luo, Yue, Amaba, Ben, Swope, William, Hu, Boyi]
通讯作者:
Hu, Boyi
Electric Vehicle Battery End-of-Use Recovery Management: Degradation Prediction and Decision Making
电动汽车电池报废回收管理:退化预测和决策
DOI:
10.1115/msec2022-85536
发表时间:
2022
期刊:
the ASME Manufacturing Science and Engineering Conference (MSEC
影响因子:
--
作者:
[Zhao, Yixin, Behdad, Sara]
通讯作者:
Behdad, Sara
Optimization-Based Disassembly Sequence Planning Under Uncertainty for Human–Robot Collaboration
不确定性下基于优化的人机协作拆卸顺序规划
DOI:
10.1115/1.4055901
发表时间:
2023
期刊:
Journal of Mechanical Design
影响因子:
3.3
作者:
[Liao, Hao-yu, Chen, Yuhao, Hu, Boyi, Behdad, Sara]
通讯作者:
Behdad, Sara
State of Health Estimation of Electric Vehicle Batteries Using Transformer-based Neural Network
使用基于变压器的神经网络估计电动汽车电池的健康状态
DOI:
--
发表时间:
2023
期刊:
IDETC/CIE2023
影响因子:
--
作者:
[Zhao, Yixin, Behdad, Sara]
通讯作者:
Behdad, Sara
共 14 条
Collaborative Research: DESC: Type 1: Software-Hardware Recycling and Repair Dataset Infrastructure (SHReDI) for Sustainable Computing
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批准号:2324950
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项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2023
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负责人:Sara Behdad
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依托单位:
Collaborative Research: Improving Design for Additive Manufacturing through Physically-integrated Design Concepts Generated from Computationally Efficient Graph Coloring Techniques
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批准号:2017968
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项目类别:Standard Grant
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资助金额:$15.14万
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财政年份:2020
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负责人:Sara Behdad
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依托单位:
GOALI: Data Driven Remanufacturing: Foundation for Modeling the Impact of Product Middle-of-Life Data on End-of-Life Recovery Decisions
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批准号:2017971
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项目类别:Standard Grant
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资助金额:$14.83万
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财政年份:2020
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负责人:Sara Behdad
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依托单位:
GOALI: Data Driven Remanufacturing: Foundation for Modeling the Impact of Product Middle-of-Life Data on End-of-Life Recovery Decisions
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批准号:1705621
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项目类别:Standard Grant
-
资助金额:$28.86万
-
财政年份:2017
-
负责人:Sara Behdad
-
依托单位:
Collaborative Research: Improving Design for Additive Manufacturing through Physically-integrated Design Concepts Generated from Computationally Efficient Graph Coloring Techniques
-
批准号:1727190
-
项目类别:Standard Grant
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资助金额:$29.24万
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财政年份:2017
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负责人:Sara Behdad
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依托单位:
GOALI: Remediating E-waste Problems by Considering Consumer Behavior in Design for Multiple Life Cycles and Design for Ease of Return
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批准号:1435908
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项目类别:Standard Grant
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资助金额:$27.99万
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财政年份:2014
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负责人:Sara Behdad
-
依托单位:
NSF CAREER Proposal Writing Workshop at the 2014 ASME International Design Engineering Technical Conferences; Buffalo, New York, 19 August 2014
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批准号:1445161
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项目类别:Standard Grant
-
资助金额:$1.0万
-
财政年份:2014
-
负责人:Sara Behdad
-
依托单位:
国内基金
海外基金
转HTFα对脊髓继发性损伤和微循环重建的影响
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批准号:39970755
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项目类别:面上项目
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资助金额:13.0万元
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批准年份:1999
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负责人:毛伯镛
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依托单位: