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

点击翻译按钮获取中文摘要

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)