FACULTY OF ENGINEERING

Department of Industrial Engineering

IE 335 | Course Introduction and Application Information

Course Name
Simulation
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 335
Spring
2
2
3
7

Prerequisites
  IE 234 To succeed (To get a grade of at least DD)
or MATH 236 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery face to face
Teaching Methods and Techniques of the Course Problem Solving
Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives This course aims at teaching the basic concepts and methods in developing simulation models of discreteevent dynamic and stochastic systems and enhancing all these concepts and methods by using the computer simulation modeling language ARENA.
Learning Outcomes The students who succeeded in this course;
  • Will be able to describe basic concepts in simulation modeling
  • Will be able to generate random variates using random numbers
  • Will be able to analyze queuing systems
  • Will be able to make input analyze for simulation models
  • Will be able to verify and validate simulation models
  • Will be able to make output analysis of simulation models
  • Will be able to compare alternative system designs
  • Will be able to build simulation models using ARENA software
Course Description This course covers basic principles in developing discrete event simulation models and also emphasizes how to analyze and interpret the results of computer simulation experiments.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction to Simulation-Basic Concepts, Systems Analysis Chapter 1, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
2 Introduction to Simulation-Types of Models, Steps of a Simulation Project Chapter 1, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
3 Generation of Random Arrivals and Random Service Times in Spreadsheet, Single-Server Queue Simulation, Performance Measures Chapter 2, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.Chapter 2, Kelton et al. Simulation with Arena, McGraw-Hill, 6th Ed., 2015.
4 Simulation Examples in Spreadsheet, Output Analysis of Output Results Chapter 2, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.Chapter 2, Kelton et al. Simulation with Arena, McGraw-Hill, 6th Ed., 2015.
5 Random Number and Random Variate Generation, Queueing Models Chapter 7-8, Chapter 6, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
6 Input Modeling-Specifying Distributions with Data, Histograms, QQ Plots Chapter 9, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
7 Input Modeling-Parameter Estimation, Chi-Sq, KS tests Chapter 9, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
8 Verification and Validation of Simulation Models Chapter 10, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
9 Output Analysis-Terminating Simulations Chapter 11, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.Bölüm 6, Kelton et al. Simulation with Arena, McGraw-Hill, 6th Ed., 2015.
10 Output Analysis-Nonterminating Simulations Chapter 11, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.Bölüm 7, Kelton et al. Simulation with Arena, McGraw-Hill, 6th Ed., 2015.
11 Comparison of Alternative System Designs Chapter 12, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
12 Comparison of Alternative System Designs Chapter 12, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
13 Simulation Methods, Softwares Chapter 4, Banks et al. Discrete Event System Simulation, 5th Ed., 2014.
14 Presentations
15 Review of Semester
16 Final Exam

 

Course Notes/Textbooks

Banks, J., Carson II, J. S., Nelson, L. B., and Nicol M. D. Discrete-Event System Simulation, Fifth Edition, Pearson Inc. 2014. ISBN: 978-1-292-02437-0.

Kelton, W.D., Sadowski, R. P. and Zupick, N.B. Simulation With ARENA, McGraw-Hill, Inc., Sixth Edition, 2015. ISBN: 978-1-259-25436-9.

Suggested Readings/Materials

Pegden, D.C., Shannon, E.R. and Sadowski P.R. Introduction to Simulation Using SIMAN, McGrawHill, Inc. 1995. ISBN: 978-0071138109.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
1
10
Project
1
15
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
45
Total

Weighting of Semester Activities on the Final Grade
4
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
2
32
Study Hours Out of Class
14
4
56
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
1
10
10
Project
1
14
14
Seminar / Workshop
0
Oral Exam
0
Midterms
1
30
30
Final Exam
1
36
36
    Total
210

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.

X
2

To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques.

X
4

To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.

X
5

To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.

X
6

To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.

X
7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions

8

To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.

9

To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.

10

To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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