MS Industrial Engineering

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Program Learning Outcomes

After successfully completing the requirements of the Master of Science in Industrial Engineering, students will be able to:

  1. Summarize and synthesize state-of-the art knowledge in a selected topic in the field of Industrial and Manufacturing Engineering.
  2. Apply scientific methods to investigate industry-driven research projects (problem articulation; hypothesis formulation; data collection, management, and analysis; implementation and dissemination of results).
  3. Make data-driven engineering decisions.
  4. Communicate appropriate information in both written and oral format, based on the audience setting and audience’s background.
  5. Work productively, respectfully, and professionally as a member of a team; exhibit leadership, ethical conduct, and community values.

The MS IE program has flexible curriculum allowing the student a wide choice in course selection. The program requires a minimum 45 quarter credits of course work in the 400 or 500 level. Of the 45 units, 22 are technical electives. Student can choose technical elective courses from the Industrial and Manufacturing Engineering (IME) department as well as outside the IME department. Flexibility is emphasized so that the student and his/her advisor can structure a degree plan tailored to the individual needs of the student. Only those letter-graded courses count toward satisfying the total unit requirement for the degree. Courses on a credit/no credit basis are not allowed in the formal study plan. No audit credits are permitted.

The MS IE program requires a thesis; the student’s thesis topic must be approved by his/her graduate committee, consisting of three committee members. Both an oral defense and a written thesis are required. The thesis will be reviewed by the Graduate Education Office and published at the Digital Commons. 

Required Courses
IME 503Applied Statistical Methods in Engineering 14
IME 507Graduate Seminar2
IME 556Technological Project Management 24
IME 580Manufacturing Systems 34
IME 599Thesis9
Approved Electives
Select from the following 4, 522
Individual Study
Systems Engineering I
Systems Engineering II
Advanced Information Systems for Operations
Design of Experiments
Change Management for Engineering Leaders
Advanced Operations Research
Applied Reliability Engineering
Applied Human Factors
Advanced Topics in Engineering Economy
Advanced Topics in Simulation
Large-Scale Optimization
Network Analysis and Optimization
Predictive Data Analytics for Engineers
Selected Advanced Topics
Selected Advanced Laboratory
Engineering Entrepreneurship
Statistical Analysis of Time Series
Categorical Data Analysis
Applied Multivariate Statistics
Statistical Computing with SAS
Statistical Computing with R
Total units45