Online Master of Science in Industrial Engineering (MS)
Industrial Engineering
Program Overview
Are you interested in strengthening your industrial engineering skills? The University of Tennessee, Knoxville, offers an online master’s degree in industrial engineering with courses covering various topics. Offered entirely online with both asynchronous and synchronous classes, this distance learning program is ideal for working professionals. Expand your knowledge across various engineering areas while earning your online MS in Industrial Engineering.
Why Choose Industrial Engineering?
This program is designed for working professionals interested in strengthening their knowledge of industrial engineering. Our courses cover a broad range of topics, such as engineering economics, engineering management, operations research, data analytics, and Lean systems.
Online learners are able to attend online classes in real-time or watch the recordings, which enable students to work around work and home commitments.
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Featured Courses
Students will have the opportunity to take a wide range of engineering-based courses during the completion of their MS in Industrial Engineering degree. Here is an example of the courses offered:
Application of classical statistical techniques to industrial engineering problems. Statistics and statistical thinking in managerial context of organizational improvement; descriptive statistics and distribution theory; relationship between statistical process control techniques and classical statistical tools; parameter estimation and hypothesis testing; goodness-of-fit testing; linear regression and correlation; analysis of variance; single and multiple factor experimental design.
Application of engineering economic analysis in complex decision situations. Inflation and price changes; uncertainty evaluation using non-probabilistic techniques; capital financing and project allocation; evaluations involving equipment replacement, investor-owned utilities, and public works projects; probabilistic risk analysis including computer simulation and decision trees; multi-attribute decision analysis; and other advanced topics.
The seminar provides an opportunity for Master’s and Doctoral students to acquaint themselves with research being conducted by faculty and graduate students in the Industrial and Systems Engineering Department, as well as select campus-wide and off-campus researchers from academia and industry. Research work and relevant results are presented in a professional environment that promotes continued interaction among interested parties.
Development and application of fundamental deterministic optimization methods, including linear programming, dynamic programming, introductory integer programming, basic game theory, and classical optimization theory applied to constrained and unconstrained models.
