IE571 SYSTEM SIMULATION
| Course Code: | 5680571 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Industrial Engineering |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Assist.Prof.Dr NADER GHAFFARINASAB |
| Offered Semester: | Fall or Spring Semesters. |
Course Objectives
At the end of the course, the students will be able to
1. comprehend and apply the statistical methods for determining and generating the input parameters of stochastic, dynamic, discrete event simulation.
2. comprehend and apply the statistical methods for analyzing the output of stochastic, dynamic, discrete event simulation to predict the system behavior and to compare the system alternatives.
Course Content
Simulation methodology and its comparison with other techniques, discrete change simulation concepts. Selecting input distributions, random variate generation, statistical analysis of output. Selected applications of simulation.(R)
Course Learning Outcomes
At the end of the course the students will
1.1. understand how random number generators work, what conditions they should satisfy to generate statistically acceptable random numbers, and how to test them.
1.2. learn how to select continuous and discrete input probability distributions by using statistical methods and tools.
1.3. learn how to generate continuous and discrete random variates from input probability distributions, given a random number generator.
2.1. understand simulation output analysis requirements and apply statistical output analysis methods for terminating and steady-state simulations.
2.2. learn simulation specific statistical methods for comparing and selecting system alternatives.
2.3. understand the experimental design issues associated with simulation and the simulation optimization concepts.
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | Specialize with advanced knowledge in selected areas of Industrial Engineering; such as Production and Operations Management, Supply Chain Management, Business Analytics and Information Systems, Decision Sciences and Operational Research, Quality Management, Human Factors and Ergonomics, and Strategy and Industrial Economics. | ✔ | |||
| 2 | Have advanced ability to formulate and solve industrial engineering problems. | ✔ | |||
| 3 | Be able to systematically acquire new scientific knowledge to design and improve socio-technical systems. | ✔ | |||
| 4 | Be able to conduct scientific research in industrial engineering. | ✔ | |||
| 5 | Be able to apply critical reasoning in their professional careers. | ✔ | |||
| 6 | Appreciate the academics ethics. | ✔ | |||