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:
2026533
负责人:
Minghui Zheng
金额:
$148.58万
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
人类技术前沿的未来工作(FW-HTF)项目将推进有效的人机协作(HRC),以降低电子再制造成本并提高操作员安全性,同时考虑再制造环境的高度复杂的非结构化性质。资源的稀缺性、环境法规以及从回收有价值的材料和部件中获得的潜在利润促使人们考虑最终使用产品的回收和再制造。然而,存在与拆卸的劳动密集型性质相关的重大挑战,拆卸是关键再制造操作(如再利用,维修,维护和回收)的组成部分。该项目的重点是机器人辅助拆卸,以提高生产率,同时提高工作满意度并确保工人安全。今天,拆卸仍然是一个主要的劳动密集型过程,需要直接接触许多可能对人体健康有害的元素。该研究将促进人类和机器人以安全和互补的方式分配任务,合作和互动的方式的基本理解。研究结果的预期好处包括提高再制造工人的生活质量,增加回收和减少废旧电子材料的浪费,创造新的制造业就业机会,减少对外国战略材料来源的依赖,以及增加国内收获的稀土元素库存。多学科研究跨越机器人技术,可持续设计,人为因素,数据科学和劳动经济学之间的界限,通过布法罗大学(UB)和佛罗里达大学(UF)之间的共同努力。该研究将通过教育和推广活动,如K12学生研讨会,两个机构的课程开发,研究生的及时培训以及一系列针对行业和学术界的研讨会,对工程教育和劳动力发展产生积极影响。该项目的重点是推进一个集成框架,以安全,互补和互动的方式利用人类和机器人的能力,为再制造行业设计一个经济可行的拆卸系统。研究团队将通过在未来技术、未来工人和未来工作的背景下实施五个相互依赖的研究任务,对协同拆卸系统进行基础研究:(1)工作环境监测与人体运动预测,(2)规划,学习和控制协作机器人,(3)拆卸序列规划下的不确定性和探索HRC启发的设计准则,(4)人-机器人系统集成;(5)再制造环境中HRC的经济影响建模和预测。具体的知识差距,解决产品设计指南,人力资源管理,职业安全标准,再制造劳动力市场之间的相互作用。融合的研究方法将允许迭代调整和增强的协作拆卸系统在未来的再制造工厂中实施。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
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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DOI:
10.1016/j.ifacol.2022.10.490
发表时间:
2022
期刊:
IFAC-PapersOnLine
影响因子:
--
作者:
[Chang Liu;Wansong Liu;Zhu Chen;Minghui Zheng]
通讯作者:
Chang Liu;Wansong Liu;Zhu Chen;Minghui Zheng
DOI:
10.1109/tmech.2022.3173167
发表时间:
2022-12
期刊:
IEEE/ASME Transactions on Mechatronics
影响因子:
--
作者:
[Wansong Liu;Xiao Liang;Minghui Zheng]
通讯作者:
Wansong Liu;Xiao Liang;Minghui Zheng
A Review of Prospects and Opportunities in Disassembly With Human–Robot Collaboration
人机协作拆卸的前景和机遇回顾
DOI:
10.1115/1.4063992
发表时间:
2024
期刊:
Journal of Manufacturing Science and Engineering
影响因子:
--
作者:
[Lee, Meng-Lun, Liang, Xiao, Hu, Boyi, Onel, Gulcan, Behdad, Sara, Zheng, Minghui]
通讯作者:
Zheng, Minghui
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
DOI:
10.1109/tsmc.2022.3185889
发表时间:
2023-01
期刊:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
影响因子:
--
作者:
[Meng-Lun Lee;Wansong Liu;S. Behdad;Xiao Liang;Minghui Zheng]
通讯作者:
Meng-Lun Lee;Wansong Liu;S. Behdad;Xiao Liang;Minghui Zheng
共 11 条
CAREER: Facilitating Autonomy of Robots Through Learning-Based Control
-
批准号:2422698
-
项目类别:Continuing Grant
-
资助金额:$57.11万
-
财政年份:2024
-
负责人:Minghui Zheng
-
依托单位:
Collaborative Research: Road Information Discovery through Privacy-Preserved Collaborative Estimation in Connected Vehicles
-
批准号:2422579
-
项目类别:Standard Grant
-
资助金额:$28.85万
-
财政年份:2024
-
负责人:Minghui Zheng
-
依托单位:
NRI/Collaborative Research: Robotic Disassembly of High-Precision Electronic Devices
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批准号:2422640
-
项目类别:Standard Grant
-
资助金额:$56.49万
-
财政年份:2024
-
负责人:Minghui Zheng
-
依托单位:
NRI/Collaborative Research: Robotic Disassembly of High-Precision Electronic Devices
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批准号:2132923
-
项目类别:Standard Grant
-
资助金额:$56.49万
-
财政年份:2022
-
负责人:Minghui Zheng
-
依托单位:
CAREER: Facilitating Autonomy of Robots Through Learning-Based Control
-
批准号:2046481
-
项目类别:Continuing Grant
-
资助金额:$57.11万
-
财政年份:2021
-
负责人:Minghui Zheng
-
依托单位:
Collaborative Research: Road Information Discovery through Privacy-Preserved Collaborative Estimation in Connected Vehicles
-
批准号:2030375
-
项目类别:Standard Grant
-
资助金额:$28.85万
-
财政年份:2020
-
负责人:Minghui Zheng
-
依托单位:
FW-HTF-P: Human-Robot Collaboration in Disassembly for Future Remanufacturing
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批准号:1928595
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项目类别:Standard Grant
-
资助金额:$15.0万
-
财政年份:2019
-
负责人:Minghui Zheng
-
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: