Developing the Workforce for Next-Generation Smart Manufacturing Systems: A Multidisciplinary Research Team Approach

Abstract

As real-world systems become more complex and connected, the industrial sector requires engineers who can solve problems across multiple disciplines and work with people across various educational backgrounds. This is particularly apparent in the manufacturing industry, as the integration of new manufacturing system technology requires knowledge in a diverse set of fields, such as physics, computer science, and engineering, to name a few. To properly educate the next workforce in manufacturing, engineering education needs to incorporate cross-disciplinary, project-driven learning that provides students with ample opportunities to work with cutting-edge manufacturing technology. At the University of Michigan, the Secure Cloud Manufacturing Multidisciplinary Design Program team focuses on developing the next generation of manufacturing engineers through research-driven multidisciplinary projects. A group of 7–22 students work on several multisemester-long projects that focus on providing hands-on, student-driven learning. Each semester, these students work closely with several faculty members, research scientists, postdocs, and graduate students to propose, develop, and conduct industry-relevant research projects on multiple manufacturing testbeds. Example projects have included the implementation of a smart quality-control camera, the development of digital twins for manufacturing processes, and the integration of secure cloud-based infrastructures for industrial controllers. In these highly collaborative and multidisciplinary project groups, students learn from each other, take on leadership roles, and disseminate their work through technical reports and presentations to academic and industry experts. Students leave the group with an understanding of the capabilities and needs of future manufacturing systems, ready to become, and lead, the next set of manufacturing engineers.

Towards proactive human–robot collaboration: A foreseeable cognitive manufacturing paradigm

“…With continuous information updates from AR-based digital worlds and proactive collaboration from its counterparts in the physical space, a human operator can solve problems in the manufacturing progress and conduct complex industrial tasks without specific training skills. People from various educational backgrounds, not limited to the domain of production, can ready to become the next set of manufacturing engineers with the support of inter- collaboration cognitive intelligence in HRC [30]. The second significance endows the entire HRC execution with high-level coordination and flexible allocation, both robot-to-human and human-to-robot.…”