Industrial Engineering

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 VE IND314
Admission Requirements IND373 VE IND314
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 Modeling and simulation are key tools for improving the performance of industrial systems. The purpose of this course is to give students both a conceptual and cultural practice in the field of modeling and simulation; introduce the applications of modeling and simulation to real problems and introduce students to the use of computer simulation tools.
Content Course Introduction: Basic concepts of the system, model and simulation - Learning to live with the random and unpredictable - Computer simulation
Concepts of the system, input, output, state - Taxonomy of the systems - Different approaches to system analysis - Different production systems and their problems
Modeling approach - Modeling process - Modeling method
Characteristics and interests of simulation - Monte Carlo Simulation - Random Number Generation - Time Control - Notions queue
Simulation process - Simulation techniques
Basic probabilistic simulation - Data modeling
Analysis of problems and industrial cases with the simulation by hand
Learning simulation softwares: Promodel, Servmodel, Medmodel
Steps to design a simulation project - Structuring a real project simulation
Statistical tests for model validation
Verification, validation and analysis of simulation results, examples of real industrial cases
Brief overview of simulation languages and simulation softwares
Course Learning Outcomes 1. Model complex systems
2. Recognize the usefulness of the simulation approach solving practical problems and as a tool for decision support
3. Know the Monte Carlo simulation and discrete event simulation
4. Know the statistical treatments for simulation
5. Teach simulation softwares (Promodel, Servmodel, Medmodel)
6. Develop a model and solve a simulation project in a real industrial context
7. Interpret the results of the simulation and understand the limitations and caveats about the analysis of these results
8. Collaboration and teamwork
9. Analyze and solve real industrial cases
Teaching and Learning Methods Lectures notes, exercises, project
References 1.KELTON, W.D. et A.M. LAW (2007). Simulation Modeling and Analysis, (3ème ou 4ème éditions), McGraw Hill.
2. ERKUT, H. (2000). Yönetimde Simülasyon Yaklaşımı, İrfan Yayıncılık, İstanbul.
Print the course contents
Theory Topics
Week Weekly Contents
1 Course Introduction: Basic concepts of the system, model and simulation - Learning to live with the random and unpredictable - Computer simulation
2 Concepts of the system, input, output, state - Taxonomy of the systems - Different approaches to system analysis - Different production systems and their problems
3 Modeling approach - Modeling process - Modeling method
4 Characteristics and interests of simulation - Monte Carlo Simulation - Random Number Generation - Time Control - Notions queue
5 Simulation process - Simulation techniques
6 Analysis of problems and industrial cases with the simulation by hand
7 Midterm
8 Basic probabilistic simulation - Data modeling
9 Learning simulation softwares: Promodel, Servmodel, Medmodel
10 Steps to design a simulation project - Structuring a real project simulation
11 Statistical tests for model validation
12 Verification, validation and analysis of simulation results, examples of real industrial cases
13 Brief overview of simulation languages and simulation softwares
14 Presentation of projects
Practice Topics
Week Weekly Contents
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 3 60
Contribution of final exam to overall grade 1 40
Toplam 4 100
In-Term Studies
  Number Contribution
Assignments 1 10
Presentation 0 0
Midterm Examinations (including preparation) 1 30
Project 1 20
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
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 3 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.
14 Knowledge of the problems of contemporary society X
15 Knowledge of the legal implications of the practice of industrial engineering
Activities Number Period Total Workload
Class Hours 14 3 42
Working Hours out of Class 12 2 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
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