ECONOMICS | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
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. |
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. |
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. |
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. |
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 |
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. |
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 |
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 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | As a world citizen, she is aware of global economic, political, social and ecological developments and trends. | 2 |
2) | He/she is equipped to closely follow the technological progress required by global and local dynamics and to continue learning. | 2 |
3) | Absorbs basic economic principles and analysis methods and uses them to evaluate daily events. | 2 |
4) | Uses quantitative and statistical tools to identify economic problems, analyze them, and share their findings with relevant stakeholders. | 2 |
5) | Understands the decision-making stages of economic units under existing constraints and incentives, examines the interactions and possible future effects of these decisions. | 1 |
6) | Comprehends new ways of doing business using digital technologies. and new market structures. | 2 |
7) | Takes critical approach to economic and social problems and develops analytical solutions. | 1 |
8) | Has the necessary mathematical equipment to produce analytical solutions and use quantitative research methods. | 2 |
9) | In the works he/she contributes, observes individual and social welfare together and with an ethical perspective. | 2 |
10) | Deals with economic problems with an interdisciplinary approach and seeks solutions by making use of different disciplines. | 1 |
11) | Generates original and innovative ideas in the works she/he contributes as part of a team. | 2 |