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Information
4 Credits
Available Winter term
Lecture only

Prerequisites
ST 314 and programming experience
Contact
David Kim
541.737.8858
424 Rogers Hall

Course Description

Analysis and design of integrated manufacturing systems through the application of computer modeling techniques. Model validation and verification. Application of simulation and decision support systems to management and engineering. Lec/lab.

Topics

  • Probability and statistics review
  • Monte Carlo simulation
  • Fundamental simulation concepts
  • Overview of ARENA simulation system
  • Randomness in simulation
  • Input data analysis
  • Output analysis
  • Verification and experimentation

Learning Outcomes

The student, upon completion of this course, will be able to:

  1. Identify different types of simulation models (e.g., stochastic-dynamic, Monte Carlo) and give examples of situations or problems where they are appropriate.
  2. Apply Monte Carlo simulation to enhance spreadsheet models.
  3. Identify the basic steps that are used in a simulation project.
  4. Demonstrate how to use raw data to specify simulation input parameters.
  5. Explain (to one experienced with simulation) the basic operation of most discrete event simulation computer languages and fundamental simulation concepts
  6. Explain the most common method for generating random numbers and random variates.
  7. Explain and demonstrate the need for statistical analysis of simulation output.
  8. Conduct a complete simulation study of a simple system using the Arena/Siman simulation system.