INDUSTRIAL ENGINEERING (ENGLISH, PHD) | |||||
PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
INE5126 | System Simulation | Spring Fall |
3 | 0 | 3 | 12 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Departmental Elective |
Course Level: | |
Mode of Delivery: | Face to face |
Course Coordinator : | |
Recommended Optional Program Components: | None |
Course Objectives: | This course is designed for junior level industrial engineering students to give the fundamental concepts of queuing theory and discrete systems simulation. The course provides statistics and probability concepts used in simulation, design of discrete systems simulation models, programming of simulation models, input modeling, random number generation and output analysis. |
The students who have succeeded in this course; I. Recognize the basic principles of simulation modeling. II. Define and use appropriate performance metrics when modeling a system. III. Recognize the basic concepts of a discrete event simulation model including model components, flowchart, and event list. IV. Collect and manage performance measurement data. V. Evaluate and implement simulation models using ARENA. VI. Develop simulation model that address critical research issues and/or industrial VII. Recognize how computer simulation can be used to model complex systems and solve related decision problems VIII. Apply a simulation project from start to finish |
1st Week: Introduction to Simulation modeling 2nd Week: Fundamentals of Simulation 3rd Week: Hand Simulation 4rd Week: Simulation Modeling 5th Week: Simulation Modeling 6th Week: Simulation Modeling 7th Week: Simulation Modeling 8th Week: Midterm exam 9th Week: Review of Probability 10th Week: Input modeling 11th Week: Input modeling 12th Week: Random Number Generation 13th Week: Output modeling 14th Week: Output modeling 15th Week: Summary and Conclusions |
Week | Subject | Related Preparation |
1) | Introduction to Simulation Modelling | |
1) | Input Modeling | |
2) | Fundamentals of Simulation | |
3) | Hand simulation | |
4) | Simulation Modeling | |
5) | Simulation Modeling | |
6) | Simulation Modeling | |
7) | Simulation Modeling | |
8) | Midterm Exam | |
9) | Review of Probability | |
10) | Input Modeling | |
11) | Input Modeling | |
12) | Random Number Generation | |
13) | Output Modeling | |
14) | Output Modeling | |
15) | Summary and Conclusions |
Course Notes / Textbooks: | W. D. Kelton, R. P. Sadowski, D. T. Sturrock, Simulation with Arena-5th Edition, McGraw-Hill, 2011. J. Banks, J. S. Carson II, B. L. Nelson, D.M. Nicol, Discrete-Event System Simulation, 5th Edition, Prentice Hall, 2010. |
References: | NA |
Semester Requirements | Number of Activities | Level of Contribution |
Quizzes | 2 | % 10 |
Homework Assignments | 4 | % 10 |
Project | 1 | % 20 |
Midterms | 1 | % 20 |
Final | 1 | % 40 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 40 | |
PERCENTAGE OF FINAL WORK | % 60 | |
Total | % 100 |
Activities | Number of Activities | Workload |
Course Hours | 14 | 42 |
Study Hours Out of Class | 12 | 36 |
Project | 4 | 25 |
Homework Assignments | 4 | 40 |
Quizzes | 2 | 20 |
Midterms | 1 | 2 |
Final | 2 | 27 |
Total Workload | 192 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Follows the scientific literature, analyzes it critically, and uses it effectively in solving engineering problems. | |
2) | Designs, plans, implements, and manages original projects related to the program field. | |
3) | Independently conducts studies related to the program field, assumes scientific responsibility, and evaluates the results with a critical perspective. | |
4) | Presents the results of their research and projects effectively in written, oral, and visual formats in accordance with academic standards. | |
5) | Conducts independent research on subjects requiring expertise in their field, develops original ideas, and transfers this knowledge into practice. | |
6) | Effectively uses advanced theoretical and practical knowledge specific to the program field. | |
7) | Acts in accordance with professional, scientific, and ethical values; takes responsibility by considering the social, environmental, and ethical impacts of engineering practices. |