Nicole Falkenberg

Nicole Falkenberg received her Masters degree from The University of Michigan, Ann Arbor, in Operations Research.  Before coming to Weber State University, she spent over 15 years in the aerospace and automotive industries.  In both industry and academia, her focus has been complex manufacturing systems and processes.  Her passion is operations management with a focus in the data sciences and business intelligence, more specifically descriptive and prescriptive analytics.

Education

The University of Michigan, Ann Arbor, Michigan
M.S.E. Industrial & Operations Engineering, Operations Research

Study Emphasis:

  • Stochastic dynamic programming, Markov Chains and processes, and renewal and semi-regenerative Poisson processes
  • Discrete event simulation for modeling and analysis of manufacturing and healthcare systems

The University of Michigan, Ann Arbor, Michigan
B.S.E. Industrial & Operations Engineering

Study Emphasis:

  • Optimization and queueing simulation modeling applications such as facility location, resource allocation, and workforce, inventory, and production modeling
  • Dynamics of In-Plant flows and the underlying behavior and management of manufacturing systems
  • Technische Universität Berlin, Berlin, Germany – Sustainable Engineering & Global Innovation in manufacturing

Cornell University, Ithaca, New York
Graduate Certificate in Engineering Leadership and Management

Alpha Quality Consulting, Salt Lake City, Utah
Six Sigma Black Belt

Teaching Experience

Weber State University, Ogden, UT
Director of Masters of Science in Systems Engineering MSSE Program (2021-present)

Instructor - Masters of Science in Systems Engineering MSSE (2021 – present)

  • SE 6140 Design for Operational Feasibility
  • SE 6320 Simulation Modeling and Engineering Optimization: Methods/Applications
  • SE 6110 Design Project
  • SE 6370 Requirements Engineering
  • SE 6900 Systems Engineering Principles & Practice
  • SE 6900 Digital Engineering and Current Events

Instructor – Bachelors of Science Manufacturing Systems Engineering BS (2019 – 2023)

Adjunct - Manufacturing Technology (2008-2009)

Industrial Experience

Aerospace – Large scale optimization of complex manufacturing systems, the data sciences, and business intelligence

Automotive – General Motors – In-Plant flows

Semi-conductor – Intel - CVD and PVD deposition processes

Pharmaceutical –Wyeth/Pfizer - Powder feeding and blending processes and CGMPs