Course Details

Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
5IE325SYSTEM SIMULATION3+2+04729.09.2025

 
Course Details
Language of Instruction English
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 Introducing concepts of discrete-event simulation
Fostering understanding through real-world simulation applications
Equipping students with essential computer simulation tools
Using simulation as a decision-making, comparison or estimation tool
Course Content Introductory course in computer simulation, which covers the use of simulation as a decision-making, comparison or estimation tool. The emphasis is on basic concepts and methods in developing discrete-event simulation models for stochastic and dynamic systems and on how to analyze and interpret the results of simulation experiments.
Course Methods and Techniques Face-to-face lectures and lab applications
Prerequisites and co-requisities ( IE222 or IE202 )
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Uğur Satıç ugur.satic@agu.edu.tr
Assistants Research Assist. Sami Kaya sami.kaya@agu.edu.tr
Work Placement(s) No

Recommended or Required Reading
Resources Simio Tutorial notes (Available on Canvas)
Lecture Slides (available on Canvas)
Banks, Jerry., Carson II, John S., Nelson, Barry L., and Nicol, David M., Discrete-Event System Simulation: Pearson New International Edition, Pearson Education Limited, 2013.
Simio Tutorials: https://jsmith.co/educational-modules/learning-simio-lab-series-lsls/
Course Notes Banks, Jerry., Carson II, John S., Nelson, Barry L., and Nicol, David M., Discrete-Event System Simulation: Pearson New International Edition, Pearson Education Limited, 2013.
Documents Canvasta
Assignments Canvasta
Exams Canvasta

Course Category
Field %100

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
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı 1 % 10
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı 1 % 25
Quiz/Küçük Sınav 3 % 30
Ödev 1 % 10
Final examination 1 % 25
Total
7
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Ev Ödevi 2 15 30
Kişisel Çalışma 14 2 28
Simülasyon 14 3 42
Ders dışı çalışma 14 2 28
Takım/Grup Çalışması 3 3 9
Yüz Yüze Ders 14 2 28
Ders Dışı Ara Sınav 1 15 15
Final Sınavı 1 15 15
Total Work Load   Number of ECTS Credits 7 195

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Develop simulation models
2 Analyze data and develop input models
3 Interpret the results of simulation runs
4 Compare alternative systems using simulation
5 Use simulation as an optimization tool
6 Use Simio software proficiently

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Lecture: Syllabus and how to install Simio Lab/Activity: A simulation model of Drivers’ License Office and Vehicles Reading the syllabus Reviewing Simio preparation materials On canvas
2 Introduction to Simulation Lab/Activity: Serial Manufacturing Line and Conveyors On canvas
3 Simulation Examples Lab/Activity: System Description and Initial Model and Symbols
4 Simulation Examples Lab/Activity: TV adjustment facility and Dynamic Routing Using Node Lists
5 Statistical Models in Simulation Lab/Activity: Healthcare Clinic Model
6 Input Modeling, Lab/Activity: Teamwork 1
7 Random Numbers and Random Variate Generation Lab/Activity: Simio Processes and Add-on Processes
8 Active Learning Week Lab/Activity: Teamwork 2
9 Midterm Exam Lab/Activity: Rate Tables
10 Simülasyon Modellerinin Doğrulama, Kalibrasyon ve Geçerliliği Lab/Activity: emergency department model
11 Estimation of Absolute Performance Lab/Activity: Simulation-based Optimization
12 Estimation of Absolute Performance Lab/Activity: 3D Warehouse, Defining and Using Custom Objects
13 Estimation of Relative Performance Lab/Activity: Teamwork 3
14 Estimation of Relative Performance Lab/Activity: Make-up exams

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 3 3 5 5
C2 3 3 5
C3 5
C4 3 4
C5 3 2
C6 5 2 5

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
  https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=78237&lang=en