Developing the workforce for next-generation smart manufacturing systems: A multidisciplinary research team approach

Ilya Kovalenko, Efe C. Balta, Yassine Qamsane, Patricia D. Koman, Xiao Zhu, Yikai Lin, Dawn M. Tilbury, Z. Morley Mao, Kira Barton

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)4-24
Number of pages21
JournalSmart and Sustainable Manufacturing Systems
Issue number2
StatePublished - May 27 2021

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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