Simulation (IE403) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Simulation IE403 7. Semester 2 2 0 3 5
Pre-requisite Course(s)
IE 202
Course Language English
Course Type Compulsory Departmental Courses
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 Danışment Vural
  • 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 Acquires sufficient knowledge in mathematics, natural sciences, and related engineering disciplines; gains the ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. X
2 Gains the ability to identify, define, formulate, and solve complex engineering problems; acquires the skill to select and apply appropriate analysis and modeling methods for this purpose. X
3 Gains the ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions, and applies modern design methods for this purpose. X
4 Develops the skills to develop, select, and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in industrial engineering applications; gains the ability to effectively use information technologies. X
5 Gains the ability to design experiments, conduct experiments, collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics. X
6 Acquires the ability to work effectively in intra-disciplinary and multidisciplinary teams, as well as individual work skills. X
7 Acquires effective oral and written communication skills in Turkish; at least one foreign language proficiency; gains the ability to write effective reports, understand written reports, prepare design and production reports, make effective presentations, and give and receive clear instructions. X
8 Develops awareness of the necessity of lifelong learning; gains the ability to access information, follow developments in science and technology, and continuously renew oneself.
9 Acquires the consciousness of adhering to ethical principles, and gains professional and ethical responsibility awareness. Gains knowledge about the standards used in industrial engineering applications.
10 Gains knowledge about practices in the business life such as project management, risk management, and change management. Develops awareness about entrepreneurship and innovation. Gains knowledge about sustainable development.
11 Gains knowledge about the universal and social dimensions of the impacts of industrial engineering applications on health, environment, and safety, as well as the problems reflected in the engineering field of the era. Gains awareness of the legal consequences of engineering solutions.
12 Gains skills in the design, development, implementation, and improvement of integrated systems involving human, material, information, equipment, and energy. X
13 Gains knowledge about appropriate analytical and experimental methods, as well as computational methods, for ensuring 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