Graduate Course Descriptions

The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.

5110. Advanced Manufacturing Quality Control

3.00 credits

Prerequisites: Department consent required.

Grading Basis: Graded

Concepts and techniques of real time statistical process control. Statistical analysis will primarily be conducted using software like Excel/Minitab/R. Students will be introduced to measurement system analysis and hypothesis testing techniques to obtain and test for quality data. These techniques will be applied using design of experiments. Process optimization methods like the Taguchi method will be implemented and control charts will be studied.

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5120. Advanced Manufacturing Processes and Products

3.00 credits

Prerequisites: Department consent required.

Grading Basis: Graded

Integrated analysis of traditional and non-traditional manufacturing processes. Topics include tolerance/ precision, surface finish/roughness, material properties of products such as hardness, and specific processes such as cutting, welding, metal deformation, ceramic processing, powder processing/metallurgy, and additive manufacturing.

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5130. Manufacturing Automation and Industry 4.0

3.00 credits | May be repeated for a total of 3 credits.

Prerequisites: Department consent.

Grading Basis: Graded

Theory of automation as related to manufacturing and design integration, including hardware, software, and algorithm issues involved in fast and flexible product development cycles. Topics cover automated manufacturing systems, CAD-CAM and integration, programming and simulation, robotics, reverse engineering virtual reality, and sensor fusion for machine tool monitoring.

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5140. Manufacturing Systems Planning

3.00 credits | May be repeated for a total of 3 credits.

Prerequisites: Department consent.

Grading Basis: Graded

Decision making in production, process, and warehouse environments. Topics include analysis of production flows, bottlenecks and queuing, types of manufacturing operations, aggregate production planning, lot sizes and lead times, and pull production systems, warehouse layout, and inventory management.

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5210. Data Science for Materials and Manufacturing

Also offered as: ME 5702, SE 5702

3.00 credits

Prerequisites: Undergraduate degree in engineering or computer science, departmental or unit consent required. Recommended preparation: Knowledge or coursework in probability and statistics. Ability to read, interpret and modify Python and MATLAB code. Ability to use Python and MATLAB for analyzing data for the course project.

Grading Basis: Graded

This course will provide students with data analytics skills for knowledge discovery and design optimization. The students will also learn how to apply data mining and machine learning techniques to tackle the challenges in manufacturing and computational materials engineering. Topics include basic concepts of supervised/unsupervised learning, design of experiments and data collection, material image processing, surrogate modeling, optimization and model calibration, multi-fidelity modeling, and applications of data analytics in manufacturing and computational materials engineering problems.

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5220. Composites Manufacturing

Also offered as: ME 5443

3.00 credits

Prerequisites: None.

Grading Basis: Graded

This course will provide an overview of multiple manufacturing methods for a select group of material types. Manufacturing methods will focus on production and process qualification for Aerospace Components. Students will have the opportunity to survey multiple materials, methods, and processes for part fabrication. Part evaluation methods will also be covered (destructive and non-destructive). There will be entry level exposure to manufacturing risk analysis through the use of industry standard tools (Manufacturing Flow, PFMEA, Control Plan, and PPAP).

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