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FW-HTF-P: Design of Tools and Technologies for Industry 4.0 Manufacturing Work

FW-HTF-P: Design of Tools and Technologies for Industry 4.0 Manufacturing Work
FW-HTF-P:工业 4.0 制造工作的工具和技术设计
批准号:
2026615
负责人:
Sheng-Jen Hsieh
金额:
$15.0万
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:
2020-09-01 至 2023-08-31

项目摘要

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中文摘要
翻译
随着信息技术的成熟,第四次工业革命--通常被称为工业4.0--正在兴起。Industry 4.0旨在利用技术将设计、制造和消费者活动无缝集成,从而提高生产率、可靠性和客户满意度。然而,过渡到行业4.0的过程对公司和员工都可能是具有挑战性的。公司不能在其生产系统和流程更新的同时停止运营。由于技术成本和培训劳动力的需要,过渡可能需要在几年内进行。不能适应新技术和新流程的工人有失去工作的风险。该项目将把制造业代表和研究人员聚集在一起,为未来的研究制定计划。该研究计划将为开发工具和技术奠定基础,使向工业4.0的过渡对公司来说更直接、更具成本效益,对工人来说更成功。可能的研究课题包括从传统制造系统向工业4.0系统过渡的路线图;工位和装配线的人体工程学设计工具;工人的认知虚拟助理;人机界面设计指南;以及自动生成知识和技能“人行横道”,以帮助公司确定仍然需要的现有技能和工人需要学习的新技能。拟议的规划拨款旨在制定与制造业内实施工业4.0有关的研究议程。工作领域是制造业;子领域可以包括智能设计、智能加工、智能装配、智能监控、智能控制和智能调度。工作场所就是工厂,可能包括生产线、工程设计以及检验和测试区域。工人包括在这些地区工作的工程师和操作员。拟议的规划活动将侧重于更好地了解行业需求,再加上趋同的研究方法,将为开发工具和技术奠定基础,以加强人与技术的伙伴关系,并提高工业4.0制造工作中的人的表现。主要任务将包括:(1)调查Industry 4.0制造系统的开发、应用和制约因素;以及(2)与来自不同制造部门的代表和具有制造工程、人类因素、人力资源开发、社会学和计算机科学专业知识的研究人员密切合作,制定统一的研究议程。智力优势:虽然工业4.0有许多潜在的好处,但目前,从传统制造系统过渡到工业4.0制造系统的过程代价高昂,对公司及其员工来说都充满风险。拟议的融合方法将使科学家能够从工厂技术经理那里了解在他们的公司内实施Industry 4.0的操作挑战。让具有不同专业领域的研究人员参与进来,将提供对问题的更丰富的理解和解决问题的趋同方法。更广泛的影响:到2025年,工业4.0预计将为国内GDP增加2.2万亿美元。全球制造业的运营转型价值估计为3.7T/年。为了保持竞争力,制造商需要能够迅速适应不断变化的市场,这需要有一支准备充分的劳动力。拟议的规划活动将确定可以开发的工具和技术,以实现行业4.0的成功实施,从而改善工作环境,定位工人在工作中取得成功,并提高美国公司的竞争力。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。
英文摘要
As information technology has matured, a Fourth Industrial Revolution—often referred to as Industry 4.0—is emerging. Industry 4.0 aims to use technology to integrate design, manufacturing, and consumer activities seamlessly, resulting in increased productivity, reliability and customer satisfaction. However, the process of transitioning to Industry 4.0 can be challenging to both companies and workers. Companies cannot stop operating while their production systems and processes are being updated. Due to the cost of the technology and the need to train the workforce, the transition may need to take place over a period of years. Workers who cannot adapt to the new technologies and processes risk losing their jobs. This project will bring manufacturing industry representatives and researchers together to develop a plan for future research. The research plan will lay the groundwork for development of tools and technologies to make the transition to Industry 4.0 more straightforward and cost-effective for companies and more successful for workers. Examples of possible research topics include road maps for transitioning from conventional manufacturing systems to Industry 4.0 systems; tools for ergonomic design of workstations and assembly lines; cognitive virtual assistants for workers; guidance for human interface design; and automated generation of knowledge and skill “crosswalks” to help companies identify existing skills that will still be needed and new skills that workers need to learn.The proposed planning grant aims to develop a research agenda related to the implementation of Industry 4.0 within the manufacturing industry. The work domain is manufacturing; sub-domains could include smart design, smart machining, smart assembly, smart monitoring, smart control and smart scheduling. The workplace is the factory, which could include production lines, engineering design, and inspection and testing areas. The workers include the engineers and operators who work in these areas. The proposed planning activities will focus on gaining a better understanding of industry needs which, together with a convergent research approach, will lay the groundwork for development of tools and technologies that can enhance the human-technology partnership and augment human performance in Industry 4.0 manufacturing work. Major tasks will include: (1) survey Industry 4.0 manufacturing system development, applications, and constraints; and (2) develop a convergent research agenda in close collaboration with representatives from a variety of manufacturing sectors and researchers with expertise in manufacturing engineering, human factors, human resource development, sociology, and computer science. Intellectual merit: Although Industry 4.0 has many potential benefits, at this time, the process of transitioning from a traditional manufacturing system to an Industrial 4.0 manufacturing system is expensive and fraught with risk to both the company and its workers. The proposed convergent approach will allow scientists to learn from plant technical managers about the operational challenges of implementing Industry 4.0 within their companies. Involving researchers with diverse areas of expertise will provide a richer understanding of the issues and convergent approaches to problem-solving. Broader impacts: Industry 4.0 is projected to add $2.2 trillion to domestic GDP by 2025. The value of the operational transformation to the global manufacturing industry is estimated to be $3.7T/year. To remain competitive, manufacturers need to be able to rapidly adapt to changing markets, which requires having a well-prepared workforce. The proposed planning activities will identify tools and technologies that could be developed to enable successful implementation of Industry 4.0, and thereby enhance work environments, position workers to be successful at their jobs, and increase competitiveness of U.S. companies.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.
期刊论文(1)
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会议论文
Preparing the manufacturing workforce for Industry 4.0 technology implementation
为制造业劳动力实施工业 4.0 技术做好准备
DOI: --
发表时间: 2023
期刊: American Society for Engineering Education (ASEE
影响因子: --
作者: [Hsieh, Sheng-Jen, Barger, Marilyn, Marzano, Suzy, Song, Juan]
通讯作者: Song, Juan
HSI Implementation and Evaluation Project: Undergraduate Research Experiences in Machine Learning for First Generation Students
  • 批准号:
    2345361
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2024
  • 负责人:
    Sheng-Jen Hsieh
  • 依托单位:
Technician Training for Industry 4.0 Technologies
RET Site: Machine Learning and Smart System Design
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国内基金
海外基金
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  • 批准号:
    39970755
  • 项目类别:
    面上项目
  • 资助金额:
    13.0万元
  • 批准年份:
    1999
  • 负责人:
    毛伯镛
  • 依托单位: