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Course Detail

Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
MODELLING and SIMULATION-Fall Semester3+248
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelFirst Cycle (Bachelor's Degree)
Course TypeRequired
Course CoordinatorAssoc.Prof. Yasin GÖÇGÜN
Name of Lecturer(s)Assoc.Prof. Yasin GÖÇGÜN
Assistant(s)
AimTo make students understand the real job applications and provide solutions to the job improvement processes by making simulation of them on a computer environment.
Course ContentThis course contains; Introduction to Simulation,Input Analysis,Random-Number and Random-Variate Generation,Monte Carlo Simulation Examples,Dynamic Simulation Examples,Discrete-Event Simulation in Arena - Basic Operations Validation,Discrete-Event Simulation in Arena - Detailed Operations,Output Analysis - Terminating Simulations,Discrete-Event Simulation in Arena - Intermediate Modeling,Output Analysis - Steady State Simulations,Discrete-Event Simulation in Arena - Entity Transfer,Sample Applications I,Sample Applications II,Arena Process Analyzer.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
1. Will be able to Make a hand simulation.12, 9A, E
2. Will be able to apply Monte Carlo simulation.21, 9A, E
3. Use Linear Congrential Method to generate a random number12, 9A, E
4. Will be able to make a discrete-event simulation using Arena.21, 8A, F
5. Will be able to analyze the outcomes of Arena.8, 9A, F
Teaching Methods:12: Problem Solving Method, 21: Simulation Technique, 8: Flipped Classroom Learning, 9: Lecture Method
Assessment Methods:A: Traditional Written Exam, E: Homework, F: Project Task

Course Outline

OrderSubjectsPreliminary Work
1Introduction to Simulation
2Input Analysis
3Random-Number and Random-Variate Generation
4Monte Carlo Simulation Examples
5Dynamic Simulation Examples
6Discrete-Event Simulation in Arena - Basic Operations Validation
7Discrete-Event Simulation in Arena - Detailed Operations
8Output Analysis - Terminating Simulations
9Discrete-Event Simulation in Arena - Intermediate Modeling
10Output Analysis - Steady State Simulations
11Discrete-Event Simulation in Arena - Entity Transfer
12Sample Applications I
13Sample Applications II
14Arena Process Analyzer
Resources
J. Banks, J.S. Carson, B.L. Nelson and D.M. Nicol, Discrete-Event System Simulation, 3rd Edition, Prentice Hall, 2001 W.D. Kelton, R.P. Sadowski and D.A. Sadowski, Simulation with Arena, 2nd Edition, McGraw-Hill, 2002 3. S.H. Ross, Simulation, 2nd Edition, Academic Press,1997

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems.
X
2
Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
X
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.
X
4
Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
X
5
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
X
6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
X
7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
X
8
Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
X
9
Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices.
X
10
Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
11
Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 30
Rate of Final Exam to Success 70
Total 100
ECTS / Workload Table
ActivitiesNumber ofDuration(Hour)Total Workload(Hour)
Course Hours14570
Guided Problem Solving10440
Resolution of Homework Problems and Submission as a Report11444
Term Project000
Presentation of Project / Seminar000
Quiz8216
Midterm Exam22040
General Exam13030
Performance Task, Maintenance Plan000
Total Workload(Hour)240
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(240/30)8
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.

Detail Informations of the Course

Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
MODELLING and SIMULATION-Fall Semester3+248
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelFirst Cycle (Bachelor's Degree)
Course TypeRequired
Course CoordinatorAssoc.Prof. Yasin GÖÇGÜN
Name of Lecturer(s)Assoc.Prof. Yasin GÖÇGÜN
Assistant(s)
AimTo make students understand the real job applications and provide solutions to the job improvement processes by making simulation of them on a computer environment.
Course ContentThis course contains; Introduction to Simulation,Input Analysis,Random-Number and Random-Variate Generation,Monte Carlo Simulation Examples,Dynamic Simulation Examples,Discrete-Event Simulation in Arena - Basic Operations Validation,Discrete-Event Simulation in Arena - Detailed Operations,Output Analysis - Terminating Simulations,Discrete-Event Simulation in Arena - Intermediate Modeling,Output Analysis - Steady State Simulations,Discrete-Event Simulation in Arena - Entity Transfer,Sample Applications I,Sample Applications II,Arena Process Analyzer.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
1. Will be able to Make a hand simulation.12, 9A, E
2. Will be able to apply Monte Carlo simulation.21, 9A, E
3. Use Linear Congrential Method to generate a random number12, 9A, E
4. Will be able to make a discrete-event simulation using Arena.21, 8A, F
5. Will be able to analyze the outcomes of Arena.8, 9A, F
Teaching Methods:12: Problem Solving Method, 21: Simulation Technique, 8: Flipped Classroom Learning, 9: Lecture Method
Assessment Methods:A: Traditional Written Exam, E: Homework, F: Project Task

Course Outline

OrderSubjectsPreliminary Work
1Introduction to Simulation
2Input Analysis
3Random-Number and Random-Variate Generation
4Monte Carlo Simulation Examples
5Dynamic Simulation Examples
6Discrete-Event Simulation in Arena - Basic Operations Validation
7Discrete-Event Simulation in Arena - Detailed Operations
8Output Analysis - Terminating Simulations
9Discrete-Event Simulation in Arena - Intermediate Modeling
10Output Analysis - Steady State Simulations
11Discrete-Event Simulation in Arena - Entity Transfer
12Sample Applications I
13Sample Applications II
14Arena Process Analyzer
Resources
J. Banks, J.S. Carson, B.L. Nelson and D.M. Nicol, Discrete-Event System Simulation, 3rd Edition, Prentice Hall, 2001 W.D. Kelton, R.P. Sadowski and D.A. Sadowski, Simulation with Arena, 2nd Edition, McGraw-Hill, 2002 3. S.H. Ross, Simulation, 2nd Edition, Academic Press,1997

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems.
X
2
Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
X
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.
X
4
Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
X
5
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
X
6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
X
7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
X
8
Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
X
9
Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices.
X
10
Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
11
Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 30
Rate of Final Exam to Success 70
Total 100

Numerical Data

Student Success

Ekleme Tarihi: 09/10/2023 - 10:42Son Güncelleme Tarihi: 09/10/2023 - 10:43