INE4011 System SimulationBahçeşehir UniversityDegree Programs ELECTRICAL AND ELECTRONICS ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRICAL AND ELECTRONICS ENGINEERING
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 Fall 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) Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.)
4) Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.