TÜRKÇE
ENGLISH
Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| INDUSTRIAL ENGINEERING (PhD) | |
| Code | EM500 |
| Name | Advanced Simulation Modeling |
| Term | 2019-2020 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. CENK ŞAHİN |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of this course is to examine simulation techniques as an analysis and modeling approach in industrial engineering problems. In this course, simulation models will be created in computer environment and statistical analysis methods used in simulation will be given.
Course Content
Course Content Basic Simulation Concepts, Discrete Event Simulation and Modeling Structures, Selection of Probability Distributions, Hypothesis Testing, Random Number Generators and Distributions, Random Number Generation, Simulation Software Analysis and SIMAN Simulation Language and ARENA Model Development Environment, ARENA Samples and Applications, Simulation Models Validity Tests, Output Analysis and Comparison of Alternative System Designs, Variance Reduction Technique
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learning the basics of simulation |
| LO02 | Learning data collection and distribution fitting techniques |
| LO03 | Learning the statistical methods used in simulation |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Understands, interprets and applies knowledge in his/her field domain both in-depth and in-breadth by doing scientific research in industrial engineering. | 5 |
| PLO02 | - | Acquires comprehensive knowledge about methods and tools of industrial engineering and their limitations. | 5 |
| PLO03 | - | Designs and performs analytical modeling and experimental research and analyze/solves complex matters emerged in this process. | 5 |
| PLO04 | - | Completes and applies the knowledge by using scarce and limited resources in a scientific way and integrates the knowledge into various disciplines. | 5 |
| PLO05 | - | Keeps up with the recent changes and applications in the field of Industrial Engineering and examines and learns these innovations when necessary. | 5 |
| PLO06 | - | Has the ability to propose new and/or original ideas and methods, develops innovative solutions for designing systems, components or processes. | 4 |
| PLO07 | - | Develops original definitions that will provide innovation to the field at the level of expertise for current and advanced information in the field based on graduate qualifications. | 4 |
| PLO08 | - | Designs Industrial Engineering problems, develops innovative methods to solve the problems and applies them. | 5 |
| PLO09 | - | Works in multi-disciplinary teams and takes a leading role and responsibility. | 4 |
| PLO10 | - | Identifies, gathers and uses necessary information and data. | 4 |
| PLO11 | - | Follows, studies and learns new and developing applications of industrial engineering. | 5 |
| PLO12 | - | Uses a foreign language in verbal and written communication at least B2 level of European Language Portfolio. | 4 |
| PLO13 | - | Presents his/her research findings systematically and clearly in oral and written forms in national and international platforms. | 4 |
| PLO14 | - | Understands social and environmental implications of engineering practice. | 5 |
| PLO15 | - | Considers social, scientific and ethical values in the process of data collection, interpretation and announcement of the findings. | 4 |
| PLO16 | - | Works in multi-disciplinary teams, take a leading role and responsibility and develop solutions for complex problems. | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Basic simulation concepts | Reading the lectures and lecture notes | |
| 2 | Discreate event simulation | Reading the lectures and lecture notes | |
| 3 | Probability distributions-1 | Reading the lectures and lecture notes | |
| 4 | Probability distributions-2 | Reading the lectures and lecture notes | |
| 5 | hypothesis testing | Reading the lectures and lecture notes | |
| 6 | Random number generators | Reading the lectures and lecture notes | |
| 7 | Examination of simulation software and introduction to ARENA software | Reading the lectures and lecture notes | |
| 8 | Mid-Term Exam | Reading the lectures and lecture notes | |
| 9 | Arena samples and applications-1 | Reading the lectures and lecture notes | |
| 10 | Arena samples and applications-2 | Reading the lectures and lecture notes | |
| 11 | Arena samples and applications-3 | Reading the lectures and lecture notes | |
| 12 | Arena samples and applications-4 | Reading the lectures and lecture notes | |
| 13 | Arena samples and applications-5 | Reading the lectures and lecture notes | |
| 14 | Arena samples and applications-6 | Reading the lectures and lecture notes | |
| 15 | Arena samples and applications-7 | Reading the lectures and lecture notes | |
| 16 | Term Exams | Reading the lectures and lecture notes | |
| 17 | Term Exams | Reading the lectures and lecture notes |