Master of Science in Industrial Engineering

Master of Science in Industrial Engineering Program by the University of Arizona at UTC Global Tunisia

Description

The Master of Science in Industrial Engineering can help you develop the skills you need to optimize manufacturing operations and supervise high-tech production processes. You’ll examine areas of production control that are essential to any advanced position in the field, developing practical skills that can be applied to projects of any scale.

As a student, you’ll be able to choose a complete set of electives to develop the specific skills you’re seeking, exploring only the areas that interest you most. The online master’s in industrial engineering program can provide you with an in-depth exploration of technical skills, like traffic modeling, automation, and Computer-integrated Manufacturing (CIM). Additionally, the curriculum delves into business fundamentals like cost estimation and financial modeling that can help engineering leaders keep any production line running at optimal performance. In the contemporary manufacturing climate, these skills are considered immensely valuable at all stages of the product lifecycle.

You’ll also have the opportunity to choose from a broad selection of electives as you build your academic plan and create a course of study that helps you reach your goals. Additionally, you’ll be able to choose between 3 separate paths to fulfilling your requirements, completing a hands-on project, assembling and defending a thesis, or by completing additional coursework. The online master’s in industrial engineering is incredibly flexible, as a result, and can be shaped to match your preferred learning style, academic experience, and career goals.

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Sample Courses

Wondering about the specific classes you can take in this program? See the course descriptions below

SIE 606: Advanced Quality Engineering

Advanced techniques for statistical quality assurance, including multivariate control charting, principal components analysis, economic design of acceptance sampling plans and control charts, inspection errors, and select papers from the recent literature.

SIE 608: Advanced Reliability Engineering

The course provides a comprehensive introduction to the statistical principles and methods for reliability data analysis. This course will cover parametric, nonparametric, and semiparametric methods for modeling degradation data and failure time data with different types of censoring.

SIE 631: Distributed Multi-Paradigm Simulation Systems

Emphasis on current research problems including random variate generation, modeling, language development and statistical analysis of output.

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