Simulation (IE403) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Simulation IE403 2 2 0 3 5
Pre-requisite Course(s)
IE 202
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Drill and Practice, Problem Solving, Team/Group, Project Design/Management.
Course Coordinator
Course Lecturer(s)
  • Dr. Öğr. Üyesi Gözdem DURAL SELÇUK
  • Research Assistant Şevval KILIÇOĞLU
Course Assistants
Course Objectives In this course simulation modelling and analysis will be introduced as an essential industrial engineering analysis tool.
Course Learning Outcomes The students who succeeded in this course;
  • The students will acquire the basic concepts and methodology of simulation.
  • The students will be able to design and conduct simulation experiments with the aim of developing solutions to manufacturing and service system problems.
  • The students will be able to use ARENA software as a simulation tool.
  • Students will be able to interpret simulation outputs.
  • The students will be able to develop communication and team working skills.
Course Content Simulation methodology, input analysis, random number generation, simulation models, output analysis, simulation experimental design, comparison of alternatives.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction, basic simulation modeling, exploring a simulation software [1] pages 3-17 [2] pages 3-15
2 Basic simulation modeling, modeling in a simulation software [1] pages 19-52 [2] pages 19-43
3 Basic simulation modeling, modeling in a simulation software [1] pages 19-52 [2] pages 19-43
4 Random-number generators, modeling in a simulation software [1] pages 221-236 [2] pages 49-95
5 Random-number generators, modeling in a simulation software [1] pages 221-236 [2] pages 49-95
6 Generating random variates, modeling in a simulation software [1] pages 239-263 [2] pages 49-95
7 Midterm 1
8 Selecting input probability distributions, modeling in a simulation software [1] pages 267-305 [2] pages 49-95
9 Selecting input probability distributions, modeling in a simulation software [1] pages 267-305 [2] pages 49-95
10 Selecting input probability distributions, modeling in a simulation software [1] pages 267-305 [2] pages 49-95
11 Validation and verification, modeling in a simulation software [1] pages 310-333 [2] pages 49-95
12 Output data analysis, modeling in a simulation software [1] pages 335-372 [2] pages 167-250
13 Output data analysis, modeling in a simulation software [1] pages 335-372 [2] pages 167-250
14 Midterm 2
15 Comparing alternative system configurations, modeling in a simulation software [1] pages 379-418 [2] pages 303-333
16 Project Presentations

Sources

Course Book 1. Discrete-Event System Simulation by J. Banks, J.S. Carson II, B.L. Nelson, D.M. Nicol, Pearson.
Other Sources 2. Kelton, W.D., Sadowski, R.P., Sadowski, D.A., Simulation with Arena,, McGraw-Hill, 2004 Edition (ISBN 0-07-121934X)Pegden, C.D., Shannon, R.E., Sadowski, R.P., Introduction to Simulation Using SIMAN (2nd ed.), McGraw-Hill, 1995. (QA76.9.C65 P44)
3. Pegden, C.D., Shannon, R.E., Sadowski, R.P., Introduction to Simulation Using SIMAN (2nd ed.), McGraw-Hill, 1995. (QA76.9.C65 P44)
4. Law. A.M., Kelton, W.D., Simulation Modeling and Analysis (3rd ed.), McGraw-Hill, 2000. (QA76.9.C65 L38)

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 15
Presentation - -
Project 1 20
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 40
Final Exam/Final Jury 1 25
Toplam 9 100
Percentage of Semester Work 75
Percentage of Final Work 25
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 An ability to apply knowledge of mathematics, science and engineering to Industrial Engineering; an ability to apply theoretical and practical knowledge to model and solve engineering problems. X
2 An ability to identify, formulate and solve complex engineering problems; an ability to select and apply proper analysis and modeling methods. X
3 An ability to design a complex system, process, tool or component to meet desired needs within realistic constraints; an ability to apply modern design. X
4 An ability to develop, select and put into practice techniques, skills and modern engineering tools necessary for engineering practice; an ability to use information technology effectively. X
5 An ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or disciplinary research topics. X
6 An ability to work individually, on teams, and/or on multidisciplinary teams. X
7 Ability to communicate effectively in Turkish orally and in writing; knowledge of at least one foreign language; effective report writing and understand written reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instruction. X
8 A recognition of the need for, and an ability to engage in life-long learning; an ability to use information-seeking tools and to follow the improvements in science and technology.
9 An ability to behave according to the ethical principles, an understanding of professional and ethical responsibility. Information on standards used in industrial engineering applications.
10 Knowledge of business applications such as project management, risk management and change management. A recognition of entrepreneurship, innovativeness. Knowledge of sustainable improvement.
11 Information on the effects of industrial engineering practices on health, environment and security in universal and societal dimensions and the information on the problems of the in the field of engineering of the era. Awareness of the legal consequences of engineering solutions.
12 An ability to design, development, implementation and improvement of integrated systems that include human, materials, information, equipment and energy. X
13 Knowlede on appropriate analytical, computational and experimental methods to provide system integration. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 2 32
Laboratory
Application 16 2 32
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration
Project 1 11 11
Report
Homework Assignments 2 2 4
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 8 8
Prepration of Final Exams/Final Jury 1 10 10
Total Workload 125