Simulation Modeling of Engineering Systems
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|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.|
MS in Engineering
MS in Integrated Supply Chain Management
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.
This three-credit course introduces students to simulation modeling and analysis techniques with applications to production, logistics, service, and other systems. Emphasis will be given to model building, application of basic statistical data analysis, and the use of simulation for the design, evaluation, and improvement of such systems. The available simulation software will be considered. After successfully completing this course, students should:
- Understand the major capabilities and commonly encountered limitations of discrete-event simulation for modeling systems that industrial engineers commonly encounter.
- Be able to 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.
- Be able to communicate the results of the modeling process to management and other non-specialist users of engineering analysis.
- Simulation modeling
- Simulation software
- Random number generation
- Random variate generation
- Input analysis
- Output analysis
- Comparison of alternative system configurations
- Variance-reduction methods
Your course grade will be comprised of eight discussion questions (15%), midterm exam (25% each), seven individual assignments (Homework-35%), and a term project (25%).
Assignments: 35% - 35 points total, five points each unless otherwise indicated
Term Project: 25% - 25 points
Midterm exam 25% - 25 points
Class Participation (Discussion): 15% - 15 points
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