FW-HTF-R: Fostering Learning and Adaptability of Future Manufacturing Workers with Intelligent Extended Reality (IXR)

点击翻译按钮获取中文摘要

This research project imagines the future of work in precision manufacturing where the spatial and causal reasoning and decision-making abilities of workers are augmented through teaming with intelligent extended reality (IXR) technologies. Evidence suggests that the newer wave of automation in manufacturing is not so much to replace workers but rather to complement human work to increase precision, safety, and product quality. Yet, U.S. manufacturers are not adequately addressing the changing nature of skill requirements which is anticipated to leave 2.4 million manufacturing jobs unfilled by 2030. This project will address the urgent need for breakthrough technologies that enable workplace-based learning and rapid upskilling of the manufacturing workforce on complex, cognitively demanding, and hard-to-automate tasks. The project will focus on precision machining and inspection in the aviation industry as the specific work context for building and validating the IXR technologies, which is also expected to inform the technology development in other industries such as medical, automotive, semiconductor, and defense. The convergent research team will create new technological pathways to enable intelligent worker-XR teaming and advance the fundamental understanding of its impacts on labor economy and worker learning and innovation. This project aims to create new perspectives, methods, and discoveries to unleash the full potential of America’s manufacturing workforce, and as such, strengthen national prosperity and economic competitiveness in precision manufacturing.This project brings together several disciplines, including engineering, learning sciences, social sciences, economics, computer sciences, psychology, and workforce development. The investigator team is structured to achieve multiple convergent goals across the three dimensions of the Future of Work at the Human-Technology Frontier: (1) The Future Work dimension will investigate the changes in employer skill requirements for precision manufacturing including education, years of experience, and actual skills, using a proprietary database of 160 million online job vacancies. Expert interviews, firm-level surveys, and in-depth case studies will investigate training and upskilling practices for incumbent and entry-level workers, explore accessibility of the IXR approach for certain groups of workers and firms, and identify economic barriers and opportunities for adopting the IXR technology. (2) The Future Technology dimension will advance the fundamental understanding of how new sources of multimodal data captured by XR devices, digital thread, IoT, and cloud-based analytics can be harnessed to interpret, predict, and guide the behavior of precision manufacturing workers. A novel IXR technology will be built and validated that adapts the scientific methods of computer vision, natural language understanding, and inference engines to provide intuitive and personalized assistance to workers performing complex reasoning and problem-solving tasks. (3) The Future Worker dimension will generate new knowledge about the affordances of worker-XR teaming to support the development of workers’ adaptive expertise for increasingly complex manufacturing tasks, building on research from the learning sciences that examines cognitive processes associated with complex reasoning and problem solving. It is expected that the knowledge generated in this project will elicit new pathways for the design of future collaborative human-technology systems for training adult workers beyond XR. This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to promote a deeper basic understanding of the interdependent human-technology partnership in work contexts by advancing the design of intelligent work technologies that operate in harmony with human workers.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.