PFI:BIC: Smart Factories -An Intelligent Material Delivery System to Improve Human-Robot Workflow and Productivity in Assembly Manufacturing

PFI：BIC：智能工厂 - 智能物料输送系统，可改善装配制造中的人机工作流程和生产力

• 批准号: 1632106
• 负责人: Laurel Riek
• 金额: $ 100万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1632106&HistoricalAwards=false
• 关键词: PFI; BIC; Smart; Factories; Intelligent

Manufacturing represents a quarter of all employment in the US. To reshore jobs, improve operations, and recruit, retain, and retrain skilled workers, companies are increasingly using robotics technology. Ideally, robots will not replace humans but team with them to improve productivity. However, most industrial robots are poorly integrated into human workflow, causing expensive work stoppage problems ($1.7M per hour), worker stress, and talent loss. The research goal of this project is to address this problem by designing novel methods to improve human-robot workflow and productivity in assembly manufacturing through the use of an intelligent material delivery system (IMDS), which will closely integrate with and support the manual work process. This project will investigate innovative, multi-disciplinary approaches to this research area, dramatically advancing the state-of-the art in smart manufacturing and human-centered robotics. The research team will make the following contributions to human-centered smart service systems: 1) Revolutionize the use of robotics in assembly manufacturing processes to closely support skilled human workers, enabling them to focus on tasks they value (their trade) as opposed to tasks that distract from their talent (material movement). 2) Dramatically improve the productivity and flexibility of factories through nimble, real-time scheduling of an IMDS system that dynamically incorporates real-time models of human workflow. 3) Deeply explore the socio-technical implications of having an IMDS system in the workplace, in terms of human workers' cognition, fatigue, affect, and job satisfaction. The project's approach serves as a direct contrast to industry state-of-the-art, which relies on strict bifurcation of human and robot work, and rigid delivery schedules that fail to take local trim-line variations into account. By closely integrating an IMDS into the manual work process and understanding worker and material status, the project will readily enable flexibility and reconfigurability of a human workforce, an absolute necessity in made-to-order, small-batch manufacturing settings. This project will help the US manufacturing sector dramatically improve their operations by using automation to directly support a talented, skilled workforce. It has the potential to impact all major US manufacturing sectors, including automotive, construction, healthcare, energy, and goods. It will help US companies reshore operations, as well as create new opportunities for US worker STEM skill acquisition. Furthermore, this project involves a detailed investigation of multiple human worker implications of the transition from traditional to intelligent material delivery using robotics. By understanding reactions to such change, there will be new understanding on how to optimize a system not only for workflow and task efficiency but also for the human experience. Such knowledge is critical to maintaining job satisfaction, safety and health, and long-term well-being of the human workforce.The lead institution is the University of Notre Dame, Department of Computer Science and Engineering, in collaboration with the Massachusetts Institute of Technology, Department of Aerospace and Aeronautics (Cambridge, MA) and University of Colorado at Boulder, Department of Civil, Environmental, and Architectural Engineering (Boulder, CA). The primary industrial partner is Steelcase, Inc. (Grand Rapids, MI), a large manufacturer that specializes in customizable, made-to-order furniture.This proposal is co-funded by The Directorate for Computer and Information Science and Engineering (CISE), Divisions of Information and Intelligent Systems (IIS) and Computer and Network Systems (CNS)

制造业代表美国所有就业的四分之一。为了改善工作，改善运营，招募，保留和再培训熟练的工人，公司越来越多地使用机器人技术。理想情况下，机器人将不会取代人类，而是与他们的团队来提高生产率。但是，大多数工业机器人都融入了人类工作流程中，导致昂贵的停工问题（每小时170万美元），工人压力和人才损失。 该项目的研究目的是通过设计新方法来通过使用智能材料交付系统（IMD）来提高人机工作流程和生产力来解决此问题，该方法将与手动工作过程紧密集成并支持。该项目将研究该研究领域的创新，多学科的方法，从而极大地推进了智能制造和以人为本的机器人技术的最新技术。研究团队将对以人为本的智能服务系统做出以下贡献：1）彻底改变了在组装制造过程中使用机器人技术，以密切支持熟练的人工工人，使他们能够专注于他们重视的任务（其贸易），而不是分散人才（物质运动）的任务。 2）通过敏捷的IMDS系统的实时调度大大提高工厂的生产率和灵活性，该系统动态结合了人类工作流程的实时模型。 3）深入探索在人工工人的认知，疲劳，情感和工作满意度方面，在工作场所中拥有IMDS系统的社会技术含义。该项目的方法与行业最先进的方法形成了鲜明的对比，该方法依赖于人类和机器人工作的严格分叉，以及无法考虑本地装饰线变化的严格交付时间表。通过将IMD紧密整合到手动工作过程中，并了解工人和物质状况，该项目将很容易地实现人类劳动力的灵活性和重新配置，这对于订购的小批量制造设置绝对必要。该项目将通过使用自动化直接支持有才华的，熟练的劳动力来帮助美国制造业大大改善其运营。它有可能影响美国所有主要制造业，包括汽车，建筑，医疗保健，能源和商品。它将帮助美国公司重新运营，并为美国工人STEM技能获取创造新的机会。此外，该项目涉及对使用机器人技术从传统材料传递到智能材料过渡的多个人工工人含义的详细研究。通过理解对这种变化的反应，将有新的了解如何优化系统，不仅是为了工作流程和任务效率，而且还针对人类的经验。 Such knowledge is critical to maintaining job satisfaction, safety and health, and long-term well-being of the human workforce.The lead institution is the University of Notre Dame, Department of Computer Science and Engineering, in collaboration with the Massachusetts Institute of Technology, Department of Aerospace and Aeronautics (Cambridge, MA) and University of Colorado at Boulder, Department of Civil, Environmental, and Architectural Engineering (Boulder, CA).主要工业合作伙伴是Steelcase，Inc。（密歇根州大急流城），这是一家专门从事可定制的，可定制的家具的大型制造商。该提案由计算机和信息科学与工程局（CISE），信息和智能系统（IIS）（IIS）以及计算机和网络系统（CNS）（CNS）共同资助。