Course Detail
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
MODELLING and SIMULATION | - | Fall Semester | 3+2 | 4 | 8 |
Course Program |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Required |
Course Coordinator | Assoc.Prof. Yasin GÖÇGÜN |
Name of Lecturer(s) | Prof.Dr. Hakan TOZAN |
Assistant(s) | |
Aim | To 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 Content | This 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 Kazanımları | Teaching Methods | Assessment Methods |
1. Will be able to Make a hand simulation. | 12, 9 | A, E |
2. Will be able to apply Monte Carlo simulation. | 21, 9 | A, E |
3. Use Linear Congrential Method to generate a random number | 12, 9 | A, E |
4. Will be able to make a discrete-event simulation using Arena. | 21, 8 | A, F |
5. Will be able to analyze the outcomes of Arena. | 8, 9 | A, 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
Order | Subjects | Preliminary Work |
---|---|---|
1 | Introduction to Simulation | |
2 | Input Analysis | |
3 | Random-Number and Random-Variate Generation | |
4 | Monte Carlo Simulation Examples | |
5 | Dynamic Simulation Examples | |
6 | Discrete-Event Simulation in Arena - Basic Operations Validation | |
7 | Discrete-Event Simulation in Arena - Detailed Operations | |
8 | Output Analysis - Terminating Simulations | |
9 | Discrete-Event Simulation in Arena - Intermediate Modeling | |
10 | Output Analysis - Steady State Simulations | |
11 | Discrete-Event Simulation in Arena - Entity Transfer | |
12 | Sample Applications I | |
13 | Sample Applications II | |
14 | Arena 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 | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
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 Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 30 | |
Rate of Final Exam to Success | 70 | |
Total | 100 |
ECTS / Workload Table | ||||||
Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
Course Hours | 14 | 5 | 70 | |||
Guided Problem Solving | 10 | 4 | 40 | |||
Resolution of Homework Problems and Submission as a Report | 11 | 4 | 44 | |||
Term Project | 0 | 0 | 0 | |||
Presentation of Project / Seminar | 0 | 0 | 0 | |||
Quiz | 8 | 2 | 16 | |||
Midterm Exam | 2 | 20 | 40 | |||
General Exam | 1 | 30 | 30 | |||
Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
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
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
MODELLING and SIMULATION | - | Fall Semester | 3+2 | 4 | 8 |
Course Program |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Required |
Course Coordinator | Assoc.Prof. Yasin GÖÇGÜN |
Name of Lecturer(s) | Prof.Dr. Hakan TOZAN |
Assistant(s) | |
Aim | To 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 Content | This 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 Kazanımları | Teaching Methods | Assessment Methods |
1. Will be able to Make a hand simulation. | 12, 9 | A, E |
2. Will be able to apply Monte Carlo simulation. | 21, 9 | A, E |
3. Use Linear Congrential Method to generate a random number | 12, 9 | A, E |
4. Will be able to make a discrete-event simulation using Arena. | 21, 8 | A, F |
5. Will be able to analyze the outcomes of Arena. | 8, 9 | A, 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
Order | Subjects | Preliminary Work |
---|---|---|
1 | Introduction to Simulation | |
2 | Input Analysis | |
3 | Random-Number and Random-Variate Generation | |
4 | Monte Carlo Simulation Examples | |
5 | Dynamic Simulation Examples | |
6 | Discrete-Event Simulation in Arena - Basic Operations Validation | |
7 | Discrete-Event Simulation in Arena - Detailed Operations | |
8 | Output Analysis - Terminating Simulations | |
9 | Discrete-Event Simulation in Arena - Intermediate Modeling | |
10 | Output Analysis - Steady State Simulations | |
11 | Discrete-Event Simulation in Arena - Entity Transfer | |
12 | Sample Applications I | |
13 | Sample Applications II | |
14 | Arena 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 | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
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 Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 30 | |
Rate of Final Exam to Success | 70 | |
Total | 100 |