Modeling and Simulation(IND304)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| IND304 | Modeling and Simulation | 6 | 3 | 0 | 0 | 3 | 5 |
| Prerequisites | IND373/ING242 |
| Admission Requirements | IND373/ING242 |
| Language of Instruction | Turkish |
| Course Type | Compulsory |
| Course Level | Bachelor Degree |
| Course Instructor(s) | GÜLÇİN BÜYÜKÖZKAN FEYZİOĞLU gulcin.buyukozkan@gmail.com (Email) Ufuk BAHÇECİ ubahceci@gsu.edu.tr (Email) Merve GÜLER KESMEZ gulermerve93@gmail.com (Email) |
| Assistant | |
| Objective |
Modelling and simulation are privileged tools for improving the performance of industrial systems. Thanks to the theoretical and practical knowledge gained in this compulsory course, students will be able to effectively apply modelling and simulation as a decision-making tool in industrial problems of enterprises (especially in problems based on complex systems). In this context, the objectives of the course are determined as follows: - To provide students with basic knowledge about modelling and simulation and how modelling and simulation can be used in decision making. - To provide students with an overview of how businesses can apply modelling and simulation approaches to industrial problems (especially those based on complex systems) - To enable students to learn simulation tools on computer |
| Content |
Week 1: Introduction to the course: System, model, simulation - Learning to live with randomness and uncertainty - Computer and simulation Week 2: System, input, output and state concepts - Classification of systems - System approach and analysis - Brief examination of production and service systems and their problems Week 3: Basic modelling concepts - Modelling process - Modelling methods - Properties and benefits of simulation - Queuing and waiting concepts Week 4: Introduction of Anylogic software Week 5: Monte Carlo simulation - Creation of random numbers - Simulation process - Simulation techniques Week 6: Probability concepts in simulation - Modelling of data Week 7: Analysing real problems by manual simulation Week 8 Midterm Exam Week 9: Designing a simulation project - Structuring a real simulation project Week 10: Chi-square test - Kolmogorov Smirnov test Week 11: Analysing real problems by manual simulation Week 12: Checking, validating and analysing simulation results Week 13: Examination and application of simulation case studies Week 14: Project presentations |
| Course Learning Outcomes |
Upon successful completion of this course, the student will be able to; 1. To be able to acquire basic knowledge about planning, designing, modelling and managing complex industrial systems and their applications in industry. 2. To be able to model a system, analyse the system, perform manual simulations and interpret the results obtained for the investigation of complex industrial engineering problems. 3. To be able to take a real industrial problem with teamwork and design a detailed experiment, model the system, collect data, solve the problem using a simulation tool and analyse and interpret the results obtained. 4. Analyse real problems/cases related to modelling and simulation, perform manual simulation, solve and interpret them. |
| Teaching and Learning Methods | Lectures notes, exercises, project |
| References |
1. Kelton, W.D., Law, A.M., "Simulation Modeling and Analysis", McGraw Hill, 2007. 2. Erkut, H., "Simulation Approach in Management", İrfan Publishing, Istanbul, 2000. Anylogic software for simulation: https://www.anylogic.com/use-of-simulation/ |
Theory Topics
| Week | Weekly Contents |
|---|---|
| 1 | Introduction to the course: System, model, simulation - Learning to live with randomness and uncertainty - Computers and simulation |
| 2 | System, input, output and state concepts - Classification of systems - System approach and analysis - Brief review of production and service systems and their problems |
| 3 | Basic modeling concepts - Modeling process - Modeling methods - Features and benefits of simulation - Queuing and waiting concepts |
| 4 | Introduction of Anylogic software |
| 5 | Monte Carlo simulation - Generation of random numbers - Simulation process - Simulation techniques |
| 6 | Probability concepts in simulation - Modeling data |
| 7 | Analyzing real problems with manual simulation |
| 8 | Midterm Exam |
| 9 | Designing a simulation project - Structuring a real simulation project |
| 10 | Chi-square test - Kolmogorov Smirnov test |
| 11 | Analyzing real problems with manual simulation |
| 12 | Checking, validating and analyzing simulation results |
| 13 | Examination and application of simulation case studies |
| 14 | Project presentations |
Practice Topics
| Week | Weekly Contents |
|---|---|
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Contribution to Overall Grade
| Number | Contribution | |
|---|---|---|
| Contribution of in-term studies to overall grade | 4 | 60 |
| Contribution of final exam to overall grade | 1 | 40 |
| Toplam | 5 | 100 |
In-Term Studies
| Number | Contribution | |
|---|---|---|
| Assignments | 1 | 10 |
| Presentation | 0 | 0 |
| Midterm Examinations (including preparation) | 1 | 25 |
| Project | 1 | 15 |
| Laboratory | 0 | 0 |
| Other Applications | 0 | 0 |
| Quiz | 1 | 10 |
| Term Paper/ Project | 0 | 0 |
| Portfolio Study | 0 | 0 |
| Reports | 0 | 0 |
| Learning Diary | 0 | 0 |
| Thesis/ Project | 0 | 0 |
| Seminar | 0 | 0 |
| Other | 0 | 0 |
| Toplam | 4 | 60 |
| No | Program Learning Outcomes | Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Knowledge and understanding of a wide range of basic sciences (math, physics, ...) and the main concepts of engineering | X | ||||
| 2 | Ability to combine the knowledge and skills to solve engineering problems and provide reliable solutions | X | ||||
| 3 | Ability to select and apply methods of analysis and modeling to ask, reformulate and solve the complex problems of industrial engineering | X | ||||
| 4 | Ability to conceptualize complex systems, processes or products under practical constraints to improve their performance, ability to use innovative methods of design | X | ||||
| 5 | Ability to design, select and apply methods and tools needed to solve problems related to the practice of industrial engineering, ability to use computer technology | X | ||||
| 6 | Ability to design experiments, collect and interpret data and analyze results | X | ||||
| 7 | Ability to work independently, ability to participate in working groups and have a multidisciplinary team spirit | X | ||||
| 8 | Ability to communicate effectively, ability to speak at least two foreign languages | X | ||||
| 9 | Awareness of the need for continuous improvement of lifelong learning, ability to keep abreast of scientific and technological developments to use the tools of information management | X | ||||
| 10 | Awareness of professional and ethical responsibility | X | ||||
| 11 | Knowledge of the concepts of professional life as "project management", "risk management" and "management of change" | X | ||||
| 12 | Knowledge on entrepreneurship, innovation and sustainability | |||||
| 13 | Understanding of the effects of Industrial Engineering applications on global and social health, environment and safety. | X | ||||
| 14 | Knowledge of the problems of contemporary society | X | ||||
| 15 | Knowledge of the legal implications of the practice of industrial engineering | X | ||||
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 3 | 14 | 42 |
| Working Hours out of Class | 2 | 12 | 24 |
| Assignments | 1 | 5 | 5 |
| Midterm Examinations (including preparation) | 1 | 15 | 15 |
| Project | 1 | 20 | 20 |
| Final Examinations (including preparation) | 1 | 26 | 26 |
| Total Workload | 132 | ||
| Total Workload / 25 | 5,28 | ||
| Credits ECTS | 5 | ||