Simulation Modeling of Engineering Systems

Course Number: ENGRG 7030
Course Name: Simulation Modeling of Engineering Systems (Online)
Course Description:    This introductory course is applied simulation taught at the graduate level. It is also a system analysis course. Students learn how to analyze systems and how to represent them in the simulation model. Students are expected to bring topics and problems to class and to contribute in significant discussion about the material. This is a hands-on course. Students are taught simulation theory through practice in developing more and more complex models. The course includes a range of simulation styles including: basic manual simulation (rolling dice, random number tables); simple automated simulation (use of general purpose software like BASIC, spreadsheets, macros); traditional simulation (coded programs with tabular results); real time monitoring (graphic displays during simulation); and state-of-the-art object oriented software (including two and three dimensional animation).
Prerequisites:    A calculus-based statistics course is required.
Level: Graduate
Credits: 3
Format: Online
Program: Master of Science in Engineering
Master of Science in Integrated Supply Chain Management

Registration Instructions

NOTE: The information below is representative of the course and is subject to change.  The specific details of the course will be available in the Desire2Learn course instance for the course in which a student registers.

Additional Information

Learning Outcomes
Upon completion of this course, you should be able to

  • Understand the major capabilities and commonly encountered limitations of discrete-event simulation for modeling systems that industrial engineers commonly encounter.
  • Formulate a real world problem and select an appropriate analytical technique for modeling and ultimately solving this problem.
  • Use simulation software for model development and analysis.
  • Develop experience with application of statistical data analysis methods for arriving at and supporting design and operations decisions.
  • Build and run simple discrete-event simulation models in practical situations; understand the main assumptions underlying these models; and understand what can happen when these assumptions do not hold.
  • Communicate the results of the modeling process to management and other non-specialist users of engineering analysis.
  • Recognize and deploy methods for influencing and managing project outcomes. Demonstrate how to apply effective project statusing and utilize key performance indicators.

Unit Descriptions

Topics

  • Simulation modeling
  • Simulation software
  • Random number generation
  • Random variate generation
  • Input analysis
  • Output analysis
  • Comparison of alternative system configurations
  • Variance-reduction methods

Grading Criteria for Activities

Assignment   Possible Points
Discussion Questions (8) 15% 15 points
Mid-Term Exam 25% 25 points
Individual Assignments (7 @ 5 pts. each 35% 35 points
Term Project 25% 25 points
Total: 100% 100 points

Grading Scale

A 90% - 100%
B 80% - 89%
C 70% - 79%
D 60% - 69%
F 0% - 59%

 

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