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 | Fall Spring |
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 : | Assoc. Prof. İBRAHİM MUTER |
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) | To understand and implement areas that are related with basic sciences, mathematics, and industrial engineering at a high level. | |
2) | To have expanded and deeper knowledge in the related field including the most recent developments. | |
3) | To use and evaluate knowledge with a systematic approach. | |
4) | To have high level proficiency of necessary methods and skills to reach the latest knowledge in the field and to understand the knowledge for making research studies. | |
5) | To make a comprehensive study innovating science and technology, developing new scientific method or technological product/process, implementing a known method to a new field. | |
6) | To be able to detect, design, implement, and finalize an original independent research process; to manage this process | |
7) | To be able to contribute science and technology by publishing outcomes of academic studies in reputable scholarly environments. | |
8) | To be able to evaluate scientific, technological, social and cultural developments, and to transfer these developments to society with scientific objectivity and ethical responsibility. | |
9) | To be able to conduct critical analysis, synthesis and evaluation of thoughts and developments in focusing field. | |
10) | To be Able to communicate and discuss orally, in written and visually with peers by using a foreign language at least at a level of European Language Portfolio C1 General Level. | |
11) | To be able to conduct functional interaction to solve the problems related to the field by using the strategic decision making processes | |
12) | To have effective and efficient management capabilities |