SIMULATION PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
END329	SIMULATION	5	4	3	5

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Prof. TARIK ÇAKAR
Instructor(s) of the Course Unit	Prof. TARIK ÇAKAR
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	To teach the students fundamental concepts of discrete-event simulation. A review of required probability and statistics background will be followed by the study of simulation methodology. A simulation Language, ARENA V14.70.0004, will be covered in detail, with assignments that will emphasize the capabilities of such a language.
Contents of the Course Unit:	Statistical Data Analysis, Monte Carlo Simulation, Develop Simulation Models, Design of Experiment with the Simulation Models, Output Analysis.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
To design a system in production or service systems
System model with Monte Carlo Simulation with Excel and interpret the results
Program the dynamic system simulation in Arena and evaluate the results.
Interpret the system's performance output.
Compare alternative systems.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	-	Introduction to Modeling and Simulation	Oral Presentation
2	-	Define the Service Systems and Queue Models	Oral Presentation
3	-	Monte Carlo Simulation-Service systems	Oral Presentation
4	-	Monte Carlo Simulation- Manufacturing Systems	Oral Presentation
5	-	Monte Carlo Simulation- Manufacturing Systems	Oral Presentation
6	-	Generating Random Variates	Oral Presentation
7	-	Input Analysis- Selecting Input Probability Distribution-EXCEL	Oral Presentation and application
8	-	MID-TERM EXAM	-
9	-	Input Analysis- Selecting Input Probability Distribution-ARENA	Oral Presentation and application
10	-	Simulation Modelling (ARENA)	Oral Presentation and application
11	-	Simulation Modelling (ARENA)	Oral Presentation and application
12	-	Simulation Modelling (ARENA)	Oral Presentation and application
13	-	Compare the Alternative Systems	Oral Presentation and application
14	-	Output Data Analysis	Oral Presentation
15	-	Output Data Analysis	Oral Presentation and application
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Simulation with Arena,W. D. Kelton, R. P. Sadowski, N. B. Swets, McGraw-Hill international edition, 5th ed., 2010.
Discrete Event System Simulation,J. Banks, J. S. Carson, B. L. Nelson, D. M. Nicol, Pearson Education, 3th ed., 2001

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Gain sufficient knowledge in Mathematics, Science and Industrial Engineering.						5

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Analyzes and evaluates existing application areas in the field of Industrial Engineering and develops applications for their solutions.						5

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Analyzes a system, the components of that system, the process of that system, and designs the system by examining it in line with realistic constraints and goals.						5
2	Gains the ability to model and solve engineering problems.						5

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Identifies the problems that may be encountered in the field of industrial engineering and acquires the ability to choose and apply the appropriate method to be used in problem solving.						5
2	Selects and uses technical tools necessary for industrial engineering applications; uses information technologies effectively.						5
3	Designs experiments, conducts experiments, collects data, analyzes and interprets the results to examine problems in the field of industrial engineering.						5

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Gains the ability to work effectively within a team.			2
2	Works effectively individually and takes responsibility.			2

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Accesses the necessary information for a determined problem and searches for resources for this purpose.					4
2	Has the ability to follow all developments in the field of industrial engineering and constantly renew itself.			2

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Gains oral and written communication skills and speaks at least one foreign language.			2

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Has awareness of professional and ethical responsibility.			2
2	Has knowledge about the universal and social effects of industrial engineering applications and reaches solutions by being aware of the importance of an innovative approach in solving engineering problems.				3

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	2	28
Preliminary & Further Study	14	2	28
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	14	2	28
Reading	0	0	0
Assignment (Homework)	2	5	10
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	2	2
Preparation for the Final Exam	1	8	8
Mid-Term Exam	1	2	2
Preparation for the Mid-Term Exam	1	6	6
Short Exam	2	2	4
Preparation for the Short Exam	2	3	6
TOTAL	52	0	122