MATHEMATICS
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
INE4011	System Simulation	Spring	2	2	3	6

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:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Prof. Dr. MUSTAFA ÖZBAYRAK
Course Lecturer(s):	Prof. Dr. MUSTAFA ÖZBAYRAK RA ESRA ADIYEKE Prof. Dr. FAİK TUNÇ BOZBURA
Recommended Optional Program Components:	None
Course Objectives:	This course is designed for junior level Industrial Engineering and close disciplines' students to give the fundamental concepts of modelling and analysis of discrete systems. The course aims to provide rigorous input and output analyses of the simulation model created using the statistical and probabilistic concepts as well as modelling the discrete systems, with the examples from both manufacturing and service systems using a general purpose simulation software.

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. Data collection or production from a sample data set. Statistical analysis of the sample data to estimate or approximate the probabilistic distribution and its parameters.
VI. Modelling and analysis of discrete event simulation models of both manufacturing and service systems using generic simulation program called ARENA.
VII. Developing simulation models that address critical research issues and/or industrial systems.
VIII. Recognizing how a computer simulation program can be used to model complex systems and solve related decision problems under different working conditions, which are presented through several what-if scenarios and analyses.
IX. Running a simulation model under different scenarios through either short-term but with consecutive replications or one very long run to get turely random output and their statistical analyses.
X. Apply a simulation project from start to finish following the stages, data collection or generation, designing the model, building the model, creating the working scenarios, running the simulation with multiple replications and statistical analyses of the output generated.

Course Content

This course is an alternative modelling method to mathematical optimization to model the complex systems. This course aims to teach the fundamental principles of simulation modelling, its steps, data creation, design and create a simulation model with the help of a simulation software, running the model under different system scenarios, obtaining the output as well as analysing and reporting output.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Simulation modeling
2)	A guided tour of modelling steps in Simulation.
3)	Statistics and Probability for Simulation Modelling I
4)	Statistics and Probability for Simulation Modelling II
5)	Modelling a simple system using ARENA
6)	System Modelling I
7)	System Modelling II
8)	Selecting the Input Analysis I
9)	Selecting Input Probability Distribution II
10)	System Modelling I
11)	Random Number Generation and Animasions
12)	Modelling Complex Systems
13)	Output Analysis
14)	Output Analysis II
15)	Entity Transfer in Modelling
16)	Simulation of Manufacturing Systems

Sources

Course Notes / Textbooks:	W. D. Kelton, R. P. Sadowski, D. T. Sturrock, Simulation with Arena-6th Edition, McGraw-Hill, 2015. J. Banks, J. S. Carson II, B. L. Nelson, D.M. Nicol, Discrete-Event System Simulation, 5th Edition, Prentice Hall, 2010.
References:	Lecture Notes and supporting materials collected from several academic resources as well as company reports and white papers.

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	28
Laboratory	14	28
Study Hours Out of Class	13	34
Project	3	9
Homework Assignments	2	6
Quizzes	2	18
Midterms	1	10
Final	1	12
Total Workload		145

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)	To have a grasp of basic mathematics, applied mathematics and theories and applications in Mathematics
2)	To be able to understand and assess mathematical proofs and construct appropriate proofs of their own and also define and analyze problems and to find solutions based on scientific methods,
3)	To be able to apply mathematics in real life with interdisciplinary approach and to discover their potentials,
4)	To be able to acquire necessary information and to make modeling in any field that mathematics is used and to improve herself/himself,	4
5)	To be able to tell theoretical and technical information easily to both experts in detail and non-experts in basic and comprehensible way,
6)	To be familiar with computer programs used in the fields of mathematics and to be able to use at least one of them effectively at the European Computer Driving Licence Advanced Level,
7)	To be able to behave in accordance with social, scientific and ethical values in each step of the projects involved and to be able to introduce and apply projects in terms of civic engagement,
8)	To be able to evaluate all processes effectively and to have enough awareness about quality management by being conscious and having intellectual background in the universal sense,	4
9)	By having a way of abstract thinking, to be able to connect concrete events and to transfer solutions, to be able to design experiments, collect data, and analyze results by scientific methods and to interfere,
10)	To be able to continue lifelong learning by renewing the knowledge, the abilities and the competencies which have been developed during the program, and being conscious about lifelong learning,
11)	To be able to adapt and transfer the knowledge gained in the areas of mathematics ; such as algebra, analysis, number theory, mathematical logic, geometry and topology to the level of secondary school,
12)	To be able to conduct a research either as an individual or as a team member, and to be effective in each related step of the project, to take role in the decision process, to plan and manage the project by using time effectively.