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

基本信息

项目摘要

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.
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-正在出现。工业4.0旨在利用技术将设计、制造和消费者活动无缝集成,从而提高生产力、可靠性和客户满意度。然而,向工业4.0过渡的过程对企业和工人来说都是一个挑战。公司不能在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,过渡可能需要数年时间。不能适应新技术和新工艺的工人有可能失去工作。 该项目将使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。该研究计划将为工具和技术的开发奠定基础,使企业向工业4.0的过渡更加直接和具有成本效益,并使工人更加成功。 可能的研究课题包括从传统制造系统过渡到工业4.0系统的路线图;工作站和装配线的人体工程学设计工具;工人的认知虚拟助手;人机界面设计指南;自动生成知识和技能“人行横道”,以协助公司找出现有的技能,仍然需要和新的技能,工人需要学习。拟议的规划补助金,目的是制定一个研究议程有关的实施工业4.0制造业。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。工作场所是工厂,包括生产线、工程设计、检验和测试区域。工人包括在这些领域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,再加上融合的研究方法,将为开发工具和技术奠定基础,这些工具和技术可以加强人与技术的伙伴关系,并提高工业4.0制造工作中的人类绩效。主要任务将包括:(1)调查工业4.0制造系统的开发、应用和限制;(2)与来自各种制造业的代表和具有制造工程、人因、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,制定一个融合的研究议程。智力优点: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制造系统的过程是昂贵的,对公司和工人都充满了风险。 拟议的融合方法将使科学家能够向工厂技术经理了解在其公司内实施工业4.0的运营挑战。让具有不同专门知识领域的研究人员参与进来,将使人们对问题有更深入的了解,并使解决问题的办法趋于一致。 更广泛的影响:预计到2025年,工业4.0将为国内GDP增加2.2万亿美元。运营转型对全球制造业的价值估计为3.7万亿美元/年。为了保持竞争力,制造商需要能够快速适应不断变化的市场,这需要有一支准备充分的劳动力队伍。拟议的规划活动将确定可以开发的工具和技术,以成功实施工业4.0,从而改善工作环境,使工人在工作中取得成功,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进行评估,被认为值得支持的搜索.

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
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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
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Sheng-Jen Hsieh其他文献

Solving the Inverse Heat Conduction Problem in Using Long Square Pulse Thermography to Estimate Coating Thickness by Using SVR Models Based on Restored Pseudo Heat Flux (RPHF) In-Plane Profile
  • DOI:
    10.1007/s10921-018-0535-8
  • 发表时间:
    2018-10-15
  • 期刊:
  • 影响因子:
    2.400
  • 作者:
    Hongjin Wang;Sheng-Jen Hsieh
  • 通讯作者:
    Sheng-Jen Hsieh
A hybrid method using FABRIK and custom ANN in solving inverse kinematic for generic serial robot manipulator
Review of additive manufacturing methods for high-performance ceramic materials
Algorithm and intelligent tutoring system design for programmable controller programming

Sheng-Jen Hsieh的其他文献

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{{ truncateString('Sheng-Jen Hsieh', 18)}}的其他基金

HSI Implementation and Evaluation Project: Undergraduate Research Experiences in Machine Learning for First Generation Students
HSI 实施和评估项目:第一代学生的机器学习本科研究经验
  • 批准号:
    2345361
  • 财政年份:
    2024
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant
Technician Training for Industry 4.0 Technologies
工业 4.0 技术技术人员培训
  • 批准号:
    2202201
  • 财政年份:
    2022
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
RET Site: Machine Learning and Smart System Design
RET 网站:机器学习和智能系统设计
  • 批准号:
    2206953
  • 财政年份:
    2022
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Just-in-Time, Online, Intelligent Tutoring for Automated System Integration: Developing a Problem-Solving Environment that Enhances Student Learning
自动化系统集成的即时、在线、智能辅导:开发一个增强学生学习的解决问题的环境
  • 批准号:
    2044449
  • 财政年份:
    2021
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
RET in Engineering and Computer Science Site: Research Experiences in Mechatronics, Robotics, and Industrial Automation
工程和计算机科学领域的 RET 网站:机电一体化、机器人技术和工业自动化领域的研究经验
  • 批准号:
    1300779
  • 财政年份:
    2013
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant
Understanding, Supporting, and Creating Curriculum Pathways for Industrial Automation Careers
了解、支持和创建工业自动化职业的课程路径
  • 批准号:
    1304843
  • 财政年份:
    2013
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant
REU Site: Interdisciplinary Research Experiences in Mechatronics, Robotics, and Automated System Design
REU 网站:机电一体化、机器人技术和自动化系统设计的跨学科研究经验
  • 批准号:
    1263293
  • 财政年份:
    2013
  • 资助金额:
    $ 15万
  • 项目类别:
    Continuing Grant
Portable Kit for Experiential Learning in Programmable Logic Controller Education (PortablePLC)
用于可编程逻辑控制器教育体验式学习的便携式套件 (PortablePLC)
  • 批准号:
    1246072
  • 财政年份:
    2013
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
Collaborative Research: Collaborative Learning Environment for Automated Manufacturing System Integration (CLE-ASI)
协作研究:自动化制造系统集成的协作学习环境(CLE-ASI)
  • 批准号:
    0935211
  • 财政年份:
    2009
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant
REU Site for Interdisciplinary Research on Imaging and Biomarkers
REU 影像和生物标志物跨学科研究网站
  • 批准号:
    0851666
  • 财政年份:
    2009
  • 资助金额:
    $ 15万
  • 项目类别:
    Standard Grant

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转HTFα对脊髓继发性损伤和微循环重建的影响
  • 批准号:
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  • 批准年份:
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