INE5126 System SimulationBahçeşehir UniversityDegree Programs INDUSTRIAL ENGINEERING (ENGLISH, THESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
INDUSTRIAL ENGINEERING (ENGLISH, THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
INE5126 System Simulation Fall 3 0 3 12
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

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.

Learning Outcomes

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

Course Content

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

Weekly Detailed Course Contents

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

Sources

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

Evaluation System

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

ECTS / Workload Table

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

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Process view and analytic thinking
2) managerial thinking with technical background
3) To have theoretical knowledge on operations research.
4) Awareness about the applications of operations research
5) To have ability of selection and efficient use of modern techniques, equipments and information technologies for industrial engineering
6) To be capable of designing and conducting experiments and collecting data, analyzing and interpreting results
7) To have verbal and oral effective communication skills by using visual methods in Turkish and English
8) To be aware of entrepreneurship, sustainability and innovation
9) To lead disciplinary and multi-disciplinary teams, to develop solution approaches in complex situations, to work individually and to take responsibility.
10) To have conscious of professional and ethical responsibility
11) To have conscious of necessity to lifelong learning
12) To be aware of economic and legal implications of engineering solutions
13) Economic, social and environmental responsibility while solving management problems