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Logistics Engineering Technology (LET)

Logistics Engineering Technology

Logistics Engineering Technology

Central Ohio's logistics industry needs workers with the skills to harness advances in robotics, data tracking, analytics, and autonomous vehicles. Join the next generation of supply chain problem solvers with an associate degree in Logistics Engineering Technology.

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Columbus State's new, cutting-edge multidisciplinary program in Logistics Engineering Technology combines coursework from Supply Chain Management, Engineering, and Information Technology (IT). The program mixes convenient online classes with hands-on instruction on industry-standard logic controllers, conveyors and logistics technology. And it's backed by Columbus State's 20-year track record of supply chain education.

Limitless Career Opportunities

  • Central Ohio is home to one of the nation's largest and fastest growing supply chain sectors.
  • The supply chain sector accounts for more than 9 percent of all jobs in Central Ohio.
  • Median Career Earnings between $50,000-$70,000 a year.

Breakthrough STEM Curriculum

  • Developed in partnership with over 20 Central Ohio employers.
  • Prepares students for careers as supply chain managers, industrial engineering technicians, systems analysts, and operations specialists.
  • Hybrid model delivers instruction through both in-person and online formats.
  • Interactive laboratory experiences focusing on supply chain technologies.
  • Embedded internship furthers students' problem-solving skills and employment opportunities.

 

For more information please contact LET@cscc.edu or a member of the LET team: 

Lee Blyth, Professor
Logistics Engineering Technology
lblyth@cscc.edu | (614) 287-5175

Jeremy Banta, Lead Faculty
Logistics Engineering Technology
jbanta1@cscc.edu | (614) 287-2559

Tara Sheffer, Coordinator
Logistics Engineering Technology
tsheffer@cscc.edu | (614) 287-5903

Monique Carney, Program Coordinator
Logistics Engineering Technology
mcarney8@cscc.edu | (614) 287-2233

This material is based upon work supported by the National Science Foundation under Grant No. 1400452.NSF logo