Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
5EDS303Simulation2+2+034

 
Course Details
Language of Instruction Turkish
Level of Course Unit Bachelor's Degree
Department / Program Industrial Engineering
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course The objective of this course is to equip students with the skills to analyze complex systems, create models, and evaluate the performance of these systems using simulation techniques. Students will learn to solve real-world problems by building simulation models and assessing different scenarios to support decision-making processes.
Course Content Introduction to simulation concepts and models
The simulation process and fundamental steps
Random number generation and distribution functions
Building simulation models
Introduction and use of simulation languages (e.g., ARENA, Simul8)
System performance measurement and result analysis
Simulation applications: Manufacturing systems, service sector, logistics, etc.
Verification and validation of simulation results
Scenario analysis and optimization
Course Methods and Techniques Introduction to simulation concepts and models
The simulation process and fundamental steps
Random number generation and distribution functions
Building simulation models
Introduction and use of simulation languages (e.g., ARENA, Simul8)
System performance measurement and result analysis
Simulation applications: Manufacturing systems, service sector, logistics, etc.
Verification and validation of simulation results
Scenario analysis and optimization
Course Notes:

Course notes are structured to include simulation theory, practical examples, software user guides, and various case studies.
The notes cover key topics such as building simulation models, using random numbers and distribution functions, and performing scenario analysis in detail.
Examples using simulation software like ARENA are provided for practical software lessons.
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof. Ozan Ateş tr.linkedin.com/in/atesozan ozan.ates@outlook.com.tr
Assistants Research Assist. Uğur Yılmaz ugur.yilmaz@gedik.edu.tr
Work Placement(s) No

Recommended or Required Reading
Resources Pegden, C. Dennis, Shannon, Robert E., Sadowski, Randall P., 1995, Introduction to Simulation Using SIMAN, Mc. Graw-Hill, Inc.
Kelton, W. David, Sadowski, Randall P., Sturrock, David T., 2007, Simulation With ARENA, McGraw-Hill.
Rossetti, Manuel D., 2009, Simulation Modeling and ARENA, Wiley.
Banks J., Carson J., Nelson B., Nicol D., 2001, Discrete-Event System Simulation, Prentice Hall.
Pegden, C. Dennis, Shannon, Robert E., Sadowski, Randall P., 1995, Introduction to Simulation Using SIMAN, Mc. Graw-Hill, Inc.
Kelton, W. David, Sadowski, Randall P., Sturrock, David T., 2007, Simulation With ARENA, McGraw-Hill.
Rossetti, Manuel D., 2009, Simulation Modeling and ARENA, Wiley.
Banks J., Carson J., Nelson B., Nicol D., 2001, Discrete-Event System Simulation, Prentice Hall.

Course Category
Mathematics and Basic Sciences %30
Engineering %20
Engineering Design %40
Field %10

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Assignment 1 % 40
Final examination 1 % 60
Total
2
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 4 56
Hours for off-the-c.r.stud 14 3 42
Project 1 14 14
Total Work Load   Number of ECTS Credits 4 112

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Understanding Simulation Techniques: Students will comprehend simulation concepts and techniques, understanding how they are used to analyze complex systems.
2 Modeling Skills: Students will develop the ability to create appropriate simulation models for different systems.
3 Random Number Generation and Distribution Functions: Students will gain foundational knowledge of random number generation and distribution functions and apply them in simulation models.
4 Simulation Software Proficiency: Students will acquire practical skills by effectively using simulation software like ARENA or similar tools.
5 Performance Measurement and Result Analysis: Students will develop the ability to analyze simulation results and evaluate system performance.
6 Scenario Analysis and Optimization: Students will be able to assess different scenarios and use optimization methods to develop the best solution proposals.
7 Project Management and Presentation Skills: Students will enhance their project management and presentation skills by managing a simulation project from start to finish and presenting the results effectively.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Concepts of Production, Process, System Approach and Management with Processes
2 Lean Production System, Flexible Production, Customer Focus, Product Development
3 Design of Production Planning Subsystems, Existing Physical Capacity, Existing Workforce, Existing Inventory Level, Production Process
4 Location of Main Production Planning Activities, Main Production Planning Process, Simulation in Production, Models
5 Simulation Implementation Process, Discrete and Continuous System Simulations, Statistical Behavior of Artificial Random Numbers
6 Traffic Simulation Applications, Supply Problems, Queuing Theory
7 Stochastic Models, Simulation Software for Waiting Lines
8 SIMAN Simulation Language and ARENA Model Development Environmen
9 ARENA Practice I
10 Arena Practice II
11 ARENA Practice III
12 ARENA Practice IV
13 ARENA Practice V and Project Presentation
14 Final Exam

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
All 4 4 3
C1 5 4 3
C2 5 5 3
C3 3 3 3
C4 5 5 3
C5 4 4 3
C6 4 4 3
C7 3 3 5

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