Manufacturing Analytics Engineering

The program may be completed entirely on campus, entirely online, or through a combination of on-campus and online courses.

Admission

Admission to the program requires a Bachelor of Science degree in engineering or a physical science from an accredited program with an average of B or better (GPA of 3.0 on a 4-point scale).

Students who do not meet BS degree requirements of the program should speak to the program advisor regarding the additional requirements to be met.  

Course Prerequisites

  • Course in probability and statistics (IMSE 510, Probability and Statistical Models or equivalent). The IMSE 510 requirements can be completed after admission into the program and will count as an elective toward the 30-credit degree requirement.
  • Course in engineering materials (ENGR 250 or equivalent). No credit will be given for the ENGR 250. 

Degree Requirements

The MSE in Manufacturing Analytics Engineering requires a minimum of 30 credit hours.

Minimum Grade Requirement in addition to maintaining a  minimum cumulative GPA of 3.0 or higher every semester:

  • Courses in which grades of C- or below are earned cannot be used to fulfill degree requirements.
  • A minimum of a 3.0 cumulative GPA  or higher is required at the time of graduation.

Please see Graduate Academic Policies for additional information.

Requirements

Students in the MSE-MAE program will have the option to declare one of 3 concentration areas, namely, Digital and Smart Manufacturing, Manufacturing and Quality Analytics, and Manufacturing Enterprise Management or to not declare a concentration. Each student is advised to declare a concentration according to their interest and take 4 courses in the selected concentration area.  A student may also choose not to declare a concentration and take 4 courses from any concentration areas. A thesis may be submitted in lieu of six hours of concentration courses, on approval by the program director.

Core Courses
The core courses will introduce production and operations management, product and process design, and quality engineering. . The following courses are required:
IMSE 586Big Data Aanal & Visuliztn3
IMSE 568AI for Smart Manufacturing3
EMGT 580Mgt of Prod and Proc Design3
Concentration Options
Students have the option to declare one of the following concentrations according to her/his interest and take 12 credits in the selected concentration: Digital and Smart Manufacturing, Manufacturing and Quality Analytics, or Manufacturing Enterprise Management. A student may also choose not to declare a concentration and take 4 courses from any concentration areas. A thesis may be submitted in lieu of six hours of concentration courses, on approval by the program director. See Concentration section for requirement details. 12
No Concentration Option
Select 12 credits from the following:
Devel & Interp Financial Info
Data Security and Privacy
Internet of Things and Smart Cities
Introduction to Big Data
Sustainability Science and Engineering
Computer-Integrated Mfg
Industrial Robots
Design and Analysis of Exp
Multivariate Statistics
Project Management and Control
Managing Global Programs
Quan Meth in Quality Engin
Intelligent Manufacturing
Tot Qual Mgmt and Six Sigma
Applied Data Analytics and Modeling for Enterprise Systems (* see note)
Reliability Analysis
Enterprise Information Systems (*see note)
Prod & Oper Engineering I
Eng Risk-Benefit Analysis
Program Budget, Cost Est & Con
Supply Chain Management
Bus Proc Int using Entrpr Tech (*See note)
Battery Materials, Manufacturing and Recycling
Digital Manufacturing
Organization Behavior
Strategic Sourcing (requires IMSE 580 as a prerequisite, which can be completed as an elective)
* Note: Completion of IMSE 564, IMSE 570, and IMSE 5755 leads to an SAP certification diploma.
Professional Electives
9 credits of any 500-level CECS graduate level courses will count toward satisfying the Professional Electives requirement, excluding ENGR 500 and ENGR 501. Note a student who lacks IMSE 510: Probability and Statistical Models or equivalent must choose IMSE 510 as a required elective course. 9
Total Credit Hours30

Concentration Options

The student is required to take 4 courses (12 credits) to satisfy the concentration requirement.  A thesis may be submitted in lieu of six hours of concentration courses, on approval by the program director.

Digital and Smart Manufacturing Concentration
Required Course:
ME 595Digital Manufacturing3
Select three courses from the following:9
Computer-Integrated Mfg
Industrial Robots
Intelligent Manufacturing
Prod & Oper Engineering I
Data Security and Privacy
Internet of Things and Smart Cities
Battery Materials, Manufacturing and Recycling
Sustainability Science and Engineering
Total Credit Hours12

The student is required to take 4 courses (12 credits) to satisfy the concentration requirement.  A thesis may be submitted in lieu of six hours of concentration courses, on approval by the program director.

Manufacturing Enterprise Management Concentration
Select one of the following:3
IMSE 5655Supply Chain Management3
OM 664Strategic Sourcing (requires IMSE 580 as a prerequisite, which can be completed as an elective)3
Select three courses from the following:9
IMSE 516Project Management and Control3
IMSE 517Managing Global Programs3
IMSE 5205Eng Risk-Benefit Analysis3
IMSE 5215Program Budget, Cost Est & Con3
IMSE 564Applied Data Analytics and Modeling for Enterprise Systems 13
IMSE 570Enterprise Information Systems 13
IMSE 5755Bus Proc Int using Entrpr Tech 13
ACC 505Devel & Interp Financial Info3
OB 510Organization Behavior3
1

Completion of IMSE 564, IMSE 570, and IMSE 5755 leads to an SAP certification diploma.

The student is required to take 4 courses (12 credits) to satisfy the concentration requirement.  A thesis may be submitted in lieu of six hours of concentration courses, on approval by the program director.

Manufacturing and Quality Analytics Concentration
Required Course:
IMSE 561Tot Qual Mgmt and Six Sigma3
Select three courses from the following:9
Design and Analysis of Exp
Multivariate Statistics
Quan Meth in Quality Engin
Reliability Analysis
Prod & Oper Engineering I
Introduction to Big Data
Total Credit Hours12